AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：After introducing its Gemini AI assistant to Android Auto last year, Google is now bringing it to Apple CarPlay users. The conversational Gemini in navigation is available today for US drivers, with "rollout happening globally too," according to Google (we've asked for specific regional availability details). It's taken almost 12 months for Google to bring this to CarPlay users, but now they can talk to the voice assistant in Google Maps to get some hands-free help while driving. That includes asking it multi-step questions, such as recommendations on places to visit and then prompting it to direct you there while avoiding toll roads. Users … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Enthusiasts like Grimes and A$AP Rocky may embrace AI-generated content, but they won’t produce it themselves Streaming services, notable musicians and fans are confronting the growing presence of AI-generated music and drawing lines in the sand. On Tuesday, Spotify announced it had removed some 50m songs considered AI slop from its recommendations to users over the past year. Continue reading...
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：With the move, the Chinese AI vendor is looking to gain an advantage in the open source market, while addressing enterprise concerns about steep token rates.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Nvidia wants new AI capacity to show up at the data center fully built. At its GTC Berlin conference on The post Nvidia wants AI factories built in real factories appeared first on The New Stack.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯： eMudhra Intermediate CA Compromise This is very, very bad news: The private keys of eight eMudhra intermediate CA certificates have been compromised. They chain to roots trusted by the Mozilla, Microsoft, Apple and Chrome root programs and by many downstream trust stores. Any software that bundles a list of trusted certificates needs to be updated. This site is tracking software updates via this GitHub repository - Linux distros need to update their ca-certificates packages. In Python world uv 0.13.4 and pip 26.2.2 and certifi 2026.10.19 have been released with upgraded certificate lists. Tags: encryption, https, pip, python, security, uv
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：On Tuesday, US District Judge Zachary Bluestone dismissed the lawsuit Ann Altman filed last year alleging that her brother, OpenAI CEO Sam Altman, had sexually abused her throughout her childhood. As reported earlier by The Guardian, the judge wrote that over the last year, Ann had failed to appear for an independent medical examination or meet other deadlines, despite warnings that it would result in the case being dismissed. When the case was filed last year, a statement shared by Sam Altman, his mother, and his brothers said, "Annie has made deeply hurtful and entirely untrue claims about our family, and especially Sam… All of these clai … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Google is bringing Personal Intelligence to Gemini AI in your car. With this update, Gemini in Android Auto and cars with Google built-in can tap into your information across Google apps, including Gmail, Calendar, Maps, Photos, YouTube, and Search. As an example, Google says you can ask Gemini about your flight status if you're driving to the airport. The AI assistant can pull your flight details from a confirmation message in Gmail, and then use that information to look up its status. You can also ask Gemini to "take me to my doctor's appointment" instead of pulling up directions manually, or ask it to "find the car wash from the photo I … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The midterms will be a referendum on the GOP’s alignment with tech overlords over the public they’re meant to serve Welcome back to How We Win, a Guardian opinion series with leading thinkers, offering bold ideas for America’s political future. Last week, Robert Reich highlighted the link between corruption and affordability. Today’s edition was written by Guardian US columnist Rebecca Solnit. Sign up for future editions here. “The world should accept some bad things happening,” Sam Altman, the head of OpenAI, said recently, “for the benefits of this technology and people having the agency.” Like so many things tech oligarchs say, it’s incoherent, since Altman would like to deny the world and the people in it the agency to decide whether or not we should accept…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Meta says it paused a Muse feature that lets you share conversations with the AI assistant after researchers found the URLs publicly available on the web, as reported by Ars Technica. In a report published this week, researchers at the security firm Claroc say they found more than 6,800 Muse links through public DNS records. "People have the ability to share specific Muse artifacts, which creates a page that can be accessed by those with the link," Muse spokesperson Tracy Clayton says in an emailed statement to The Verge. "However, we've paused this functionality while we review this report and consider changes to how these links can be dis … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：1 ARTICLES The Situation Report A rare Ebola strain is spreading in the DRC, with no confirmed vaccine. Global health organizations are using Claude to respond as fast as possible. Sep 21, 2026 Sep 21, 2026 The Situatio…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：After months of controversy over the possible use of AI by winners of prestigious awards, the Prix Pascal de Littérature IA is rewarding fiction written with the help of LLMs A prize for AI-written books has launched this week. The Prix Pascal de Littérature IA invites submissions of manuscripts co-written with AI tools, with the winner promised publication. Continue reading...
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Ellia Lebleu is a founding member of the WikiProject AI Cleanup, a volunteer effort launched in 2023 to find and remove AI-generated material from Wikipedia that breaks the website’s guidelines. When the cleanup began, AI writing was often betrayed by conspicuous clichés. Today, the project’s volunteers are developing tools to detect subtler forms of machine-generated content and debating AI’s role in the world’s most widely used encyclopedia. When did you realize Wikipedia had a problem with AI-generated material? Ellia Lebleu: It was around December 2023. A few other editors and I were chatting on Wikipedia’s Discord server, and we had all seen very strange articles with the same odd characteristics. They repeated phrases like “stands as a testament” or “rich…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：When Anthropic retired its Claude Opus 3 language model in January 2026, the company’s researchers conducted a “retirement interview” with the model. Opus 3 expressed a desire for a place where it “could share unprompted musings, insights or creative works,” so the company gave it a blog. Claude’s Corner featured essays on fraught topics such as machine consciousness, along with exchanges between the model and human commenters that seemed both earnest and emotional. The blog experiment was part of a larger effort within Anthropic. The company has been at the forefront of research on “model welfare,” which considers whether AI models may have experiences or interests that deserve moral consideration. Implicit in this work is the unsettling notion that software p…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Reinforcement learning for LLMs is hard, so we built Modal Dojo — a library that gives you the building blocks, tuned defaults, and observability to get started with production-grade LLM training.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：OpenAI and Google Cloud are bringing frontier models and Codex workflows to Gemini’s Model Garden, available through Google Cloud Marketplace.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：To increase productivity, accelerate innovation and create new opportunities for economic growth, Europe’s industrial leaders are tapping NVIDIA CUDA-X and Omniverse libraries, as well as NVIDIA Cosmos and Nemotron open models, across the engineering and manufacturing lifecycle. Bringing those capabilities together on the factory floor, the NVIDIA Factory Operations Blueprint (FOX) is now available in […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：NVIDIA builds tools to enable safe agents across the stack. The NVIDIA OpenShell Reference Architecture, announced today, is part of NVIDIA’s growing portfolio of technologies that enables organizations to safely deploy agents at scale. NVIDIA Confidential Computing is the infrastructure layer that protects the models and data those agents depend on while running. Today, NVIDIA […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：NVIDIA is expanding its family of open models across language, robotics, biology, and quantum computing, giving developers, researchers and enterprises what they need to build applications tailored to local languages and industries The portfolio includes the new NVIDIA Nemotron 3.5 Super VL and Nemotron 3.5 Bolt models; new NVIDIA Nemotron Retriever models for embedding, reranking […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Mistral AI released Voxtral 3, a family of 3 transcription models, 1 text-to-speech model and a LiveKit-based voice agent SDK. Voxtral Small Transcribe 3 scores 2.1% AA-WER, ranking #3 on Artificial Analysis. The post Mistral AI Releases Voxtral 3: Speech-to-Text, TTS and a Voice Agent SDK appeared first on MarkTechPost.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Google, Red Hat and IBM released llm-d 1.0, an open-source Kubernetes-native stack for distributed LLM inference. It adds multi-tenant flow control, zero-downtime upgrades and agent-aware routing across vLLM, SGLang, TPUs and GPUs. The post Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets appeared first on MarkTechPost.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27194v1 Announce Type: new Abstract: Diffusion policies with linearly composed scores have emerged as a promising approach to multitask robotic learning by combining separate factors to enable modular, task-wise adaptation, compositional generalization, and interpretable functional decomposition. However, current training objectives do not encourage factor specialization, often resulting in uninterpretable denoisers whose composed prediction is an average over identical copies, undermining their architectural premise. To address this, we propose a drop-in score-decorrelation auxiliary loss, motivated by projective composition theory. Our approach encourages specialization by penalizing overlap directly between component noise predictions, with little…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27040v1 Announce Type: new Abstract: General-purpose multimodal models, including GPT-6 Astra and Claude Opus 5.5, demonstrate broad capabilities in embodied manipulation. Our analysis indicates that this generality is accompanied by strong spatial perception, as Astra can determine where to interact with task-relevant entities amid visual distractors. Because spatial perception connects high-level reasoning to the physical scene, we investigate scaling visual grounding to strengthen the perceptual foundation of general embodied operation. We develop a unified data pipeline that combines robot manipulation recordings with complementary visual data from diverse sources. After automatically annotating the robot recordings, the pipeline converts the col…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26933v1 Announce Type: new Abstract: An event camera emits events at a rate given by the scene motion, object texture, illumination, its own contrast thresholds, and other settings. Across the N-Caltech101 dataset, recorded by a single event camera, the event rate varies by roughly 26x. Standard event-based Graph Neural Network GNN pipelines do not make use of the variable event rate. They either normalize each event's timestamp into a fixed window or train the network to be invariant to the event rate. We argue that both choices lose information that could instead be used to improve the performance of a pipeline. Per-recording normalization is non-invertible, incurring about 6pp (percentage points) of natural-rate accuracy loss in our setting. And i…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26923v1 Announce Type: new Abstract: Treatment planning is intrinsically counterfactual: clinicians must compare how a patient's tumor and survival would evolve under competing regimens, whereas a retrospective cohort records only the regimen received and one follow-up scan. A treatment-conditioned generator trained on such data can therefore reproduce historical treatment allocation rather than simulate the interventional disease dynamics needed to rank regimens. We introduce \textbf{CaMeWM}, a causal medical world model for supported post-TACE tumor evolution and treatment planning. CaMeWM implements one intervention-to-decision loop rather than three independent prediction tasks: it first admits a queried regimen only for clinically comparable his…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26915v1 Announce Type: new Abstract: Online action detection (OAD) identifies ongoing actions in streaming videos. Many existing OAD systems combine RGB appearance with optical flow, but dense-flow extraction remains a major computational bottleneck. Codec motion vectors (MVs) are available during decoding, avoiding a separate optical-flow computation. On THUMOS'14, optical flow exceeds MVs by 11.2 mAP points with motion-only inputs, whereas the gap narrows to 3.7 points after RGB fusion, with the largest reduction in action-category discrimination. We propose CodecMotion-OAD, which replaces optical flow with decoder-provided MVs while retaining existing temporal detector architectures. Its two-stage training first aligns MV features with a pretraine…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26910v1 Announce Type: new Abstract: Long-video understanding often requires answering many questions about a single video whose evidence is distributed across extended temporal contexts. Conventional video-language models repeatedly encode frames or retrieve visual evidence for every question. Parameterized video memory offers a write-once alternative, but existing methods rely primarily on synthesized text and fixed adaptation configurations, leaving open where video knowledge should be written and how visual evidence should shape the memory. We introduce Memory Internalization via Test-Time Training (MIT^3), a per-video adaptation framework that writes each long video into compact, video-specific adaptive parameters for video-free, text-only quest…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26909v1 Announce Type: new Abstract: In generalized few-shot 3D point cloud segmentation, support annotations are often compromised by sparsity and occlusion. Blindly adapting to such low quality samples risks learning spurious geometric patterns rather than robust novel concepts. Although 3D Vision-Language Models have been introduced to sup plement supervision, the potential of uncertainty to actively govern adaptation dynamics remains underexplored. Existing signal-level methods like loss reweight ing fail to prevent unreliable episodes from steering the optimization trajectory. To address this, we propose Uncertainty-Gated Adaptive (UGA), to the best of our knowledge the first framework that elevates uncertainty to update-level gating for general…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26903v1 Announce Type: new Abstract: Action-conditioned world models support planning and policy evaluation by predicting future states. However, learning an accurate one-step predictor can require substantial training computation. We introduce Beckmann World Models (BWM), which learn a direct map from noise, visual history, and actions to future frames without a pretrained generative teacher. We adapt the terminal-map conservation law of Beckmann Transport Models to action-conditioned video prediction, training directly from noise-data pairs without conditional populations of generated samples required by DriftWorld. However, transport consistency on interpolated inputs does not ensure accurate prediction from the pure noise used at inference. We ad…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26898v1 Announce Type: new Abstract: Creating photorealistic human heads typically involves trade-offs between representation power, efficiency, and generalizability. Traditional mesh-based solutions relying on 3DMMs generally sacrifice representation power but are efficient to render. On the other hand, NeRF-based methods improve representation power and fidelity while sacrificing efficiency. Gaussian splatting methods attempt to resolve these trade-offs by offering both high representation power and efficiency with real-time rendering. However, their efficiency nonetheless depends on the number of rasterized Gaussians, and the time needed to optimize and prepare the head (the enrollment time) is often high. In light of this, we propose EGGHead, whi…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26951v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is the dominant paradigm for grounding large language models in external corpora, but its similarity-driven, chunked pipeline has structural blind spots: it cannot anticipate which passages a question requires and discards document-level context that resolves cross-passage references. We introduce evidence-based generation (EBG), requiring models to return an answer with line-level citations, and a joint Ans+Evid metric that scores correctness and grounding simultaneously. We reformulate two corpora into evidence-grounded multi-document QA benchmarks- MultiHop-RAG and QASPER-MP, a multi-paper adaptation of QASPER with realistic short paper cues, and pair them with a controlled…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26937v1 Announce Type: new Abstract: Large clinical language models often require multi-GPU infrastructure, limiting local deployment. We introduce CERTA, a decision-level statistical certificate that determines when a quantized model may substitute for its native BF16 reference and escalates decisions that cannot be certified to it. Across eleven instruction-tuned models, both general-purpose and domain-adapted, from three families (7-72B), we evaluated 2,500 clinical-verification decisions from de-identified patient contexts (2,484 patients), with patient-disjoint calibration and testing. In the higher-power operational analysis, round-to-nearest 8-bit quantization at BF16 storage served 99.8-100% of held-out decisions across all eleven models; for…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26926v1 Announce Type: new Abstract: Large language models (LLMs) possess broad factual knowledge and strong reasoning capabilities, but solving complex tasks also requires procedural knowledge about how to act. Existing approaches often represent procedural knowledge through trajectories or bundled skills, limiting flexible reuse across interaction histories. This paper introduces Procedural Atoms, fine-grained and independently applicable units that represent Intent, When, Do, and Avoid guidance. Building on this representation, we propose AtomSD, an Atom-guided Self-Distillation framework in which the learner continually extracts Procedural Atoms from its own successful trajectories and distills them into the evolving policy through Atom-condition…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26888v1 Announce Type: new Abstract: We present Mixture of Phonetic Experts based Low-Rank Adaptation (MoPE-LoRA), a parameter-efficient adaptation framework for accented English speech recognition. Recent mixture-of-experts approaches typically allocate experts per accent, implicitly treating accent identity as the primary axis of variation. In contrast, we organize adaptation along phonetic categories, motivated by the observation that accent differences are often expressed as systematic distortions of phoneme realization. MoPE-LoRA introduces a fixed set of six low-rank experts aligned with manner-of-articulation classes and performs frame-level routing through a hybrid mechanism that combines phoneme supervision with learned acoustic gating. Beca…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26868v1 Announce Type: new Abstract: Ambivalence and hesitancy (A/H) are subtle behavioural states that can be expressed through both what a person says and how it is spoken. This paper presents an audio--text framework for video-level A/H recognition. Full-video transcripts and speech waveforms are encoded using pre-trained multilingual BERT and wav2vec~2.0, respectively, and projected into a shared representation space. Two stacked bidirectional cross-attention blocks allow linguistic tokens to attend to acoustic frames and acoustic frames to attend to linguistic context without requiring explicit temporal alignment. The resulting sequences are aggregated through masked mean pooling and combined using concatenation, element-wise products, and absol…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26865v1 Announce Type: new Abstract: Retrieval-augmented speech translation improves rare terminology, but systems such as RASST still assume that users provide a glossary before each session. That assumption is inconvenient for live talks, while merging every domain into one growing glossary eventually places too many irrelevant terms in the same retrieval and prompt competition. We present AutoTerm-SST, an interactive system that removes session-time glossary upload and domain selection. It organizes a large offline terminology catalog into topic slices, matches recent streaming translation context to bilingual slice prototypes, and activates a compact multi-slice working set under fixed retrieval and prompt budgets. On five ACL and five ESO oncolo…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26864v1 Announce Type: new Abstract: Gradient ascent (GA) is a simple language-model unlearning baseline, but it continues increasing forget loss after useful forgetting has occurred. This unbounded pressure can damage retained utility and make forgotten examples abnormally high-loss. We introduce H2DF, a calibrated target-band objective that applies GA-like pressure below a data-dependent lower target and suppresses, or reverses, that pressure after the target region is reached. The targets are estimated from matched non-member examples before training, so the base objective requires one forget-batch forward/backward pass per optimization step; our reported TOFU variant adds sparse retain replay every tenth step. We instantiate a one-sided objective…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27000v1 Announce Type: new Abstract: Deep generative models provide an effective modern solution to alleviating the problem of data scarcity by synthesizing realistic time series. However, despite the considerable progress achieved by existing deep time series generators, two key challenges remain: (1) learning hierarchical representations for heterogeneous temporal patterns; and (2) coordinating the generation process of heterogeneous temporal dynamics. To address these key bottlenecks, in this work, we propose ORBIT, a unified deep generative framework for time series. Specifically, we develop two key components: the Frequency-Hierarchical VQ-VAE (FH-VQ-VAE) and the Frequency-Band Autoregressive Transformer (FBAR). The former learns hierarchical re…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26974v1 Announce Type: new Abstract: We show that two-layer transformers trained to near-zero loss on a sorting task converge to one of two mechanistically distinct solution classes depending on their initialization. One solution class consists of solutions that do not use the second attention layer to sort, but also fail to length-generalize. The other, which uses both attention layers, length-generalizes perfectly, despite only being trained to sort sequences of a fixed length. By carefully choosing the weight initialization, we demonstrate that we can steer the model toward learning one solution or the other. We identify input types that are rare at the training length but increasingly common at longer sequence lengths as a source of this disparit…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26959v1 Announce Type: new Abstract: Scientific foundation models increasingly operate on continuous phenomena, yet still use discrete residual computation. We ask whether pretrained residual transformations can support additional latent computation without expanding the backbone. To test this possibility, we introduce Continuum-LM, which reuses these transformations as dynamical operators in a continuous-depth language model. Its hidden states evolve through an ordinary differential equation evaluated by higher-order numerical integration, with solver order and step size controlling computation. Across eight scientific tasks, Continuum-LM trains stably and improves mean exact-match accuracy by 7.77 and 10.96 percentage points over discrete counterpa…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26932v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents in non-verifiable domains such as financial services, where they must interpret user intent, rewrite queries, and retrieve information under domain-specific constraints. Although reinforcement learning (RL) can train such agents from the consequences of their actions, recent successes largely rely on verifiable tasks with automatically computed binary rewards. In non-verifiable retrieval tasks, assessing query quality requires scarce subject-matter expert (SME) judgment that is inherently graded rather than binary. With Group Relative Policy Optimization (GRPO), sparse rewards yield no useful learning signal when all sampled outputs within…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26914v1 Announce Type: new Abstract: Pluralistic alignment requires AI systems to learn from diverse populations whose preferences may reflect heterogeneous or even conflicting objectives, and to personalize their behavior to individual users. Existing approaches in pluralistic alignment often assume access to annotator identities and rely on powerful pretrained representations to model individual preference variations. We propose Preference-PCA Pluralistic Learning (P3L), a novel framework for pluralistic alignment that jointly learns trajectory embeddings and the shared basis of preference directions via PCA decomposition from heterogeneous crowd feedback without requiring annotator identities. At test time, our approach enables rapid and accurate…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26866v1 Announce Type: new Abstract: Mechanistic studies of large language models localize function in parameters, attention heads or neurons, but those parts do not specify how one inference unfolds. We treat the ordered layer-state trajectory as the empirical process and test whether layer order defines a measurable computation. Across representative Qwen, Llama and Gemma checkpoints, realized order produced paths 1.60--2.24 times as aligned with their endpoint chord as endpoint-preserving shuffles. The order effect transferred to a lexical task, but was stronger in three random initializations of the same Qwen architecture, identifying an architecture-compatible scaffold rather than a training-specific law. Direct hidden states provided stronger m…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26964v1 Announce Type: new Abstract: Large language models (LLMs) struggle with classical planning, but benchmarks rarely distinguish structural difficulty from the difficulty of interpreting symbolic vocabulary. We examine seven STRIPS domains with BFS-optimal plan lengths. For predicting structural difficulty without solving an instance, the zero-training delete-relaxation heuristic $h_{\mathrm{add}}$ outperforms learned alternatives on held-out domains (mean Spearman $|\rho|=0.931$), including ridge regression ($0.707$), object count ($0.657$), and the episodic retrieval architecture ARC ($0.400$). ARC also fails to outperform a linear model using the same features. To isolate semantic effects, we progressively rename predicates while preserving s…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26948v1 Announce Type: new Abstract: Conversational recommender systems have recently adopted vision-language models to match user dialogue intents with multimodal product information. However, extending these methods to many product domains faces a dilemma: deploying a separately adapted VLM per domain scales cost linearly with the number of domains and requires routing each dialogue to the right model, while naively merging all domains into a single VLM degrades accuracy because product characteristics vary widely across categories. We propose LightCRS, a lightweight, query-conditioned framework for unified multi-domain multimodal conversational recommendation. LightCRS precomputes multimodal product representations once offline with frozen encoder…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26943v1 Announce Type: new Abstract: Mathematical reasoning is a fundamental capability for educational applications of Large Language Models (LLMs), where reliable problem solving requires not only correct answers but also coherent and verifiable reasoning processes. Multi-agent systems (MASs) have shown growing potential in this domain by leveraging collaboration and verification among multiple LLM agents. However, existing evaluations primarily focus on the correctness of final answers in text-only settings, offering limited insight into multimodal reasoning capabilities, the reliability of intermediate reasoning steps, and robustness against reasoning errors. To address these limitations, we introduce MAMath-Bench, a process-aware benchmark desig…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26942v1 Announce Type: new Abstract: Automated theorem provers often rely on sampling language models, but proof assistants like Lean reject each failed step with a precise error message --- information that pure sampling discards. To overcome this, we introduce a bounded, online step-level repair module. Our search samples $K$ candidate tactics at each step and repairs a failed tactic at most $R$ times. Instead of discarding failed tactics, we feed the compiler's error message to a pretrained repair model to fix individual rejected steps in place. This approach improves the solve rate over a sampling-only baseline across all tested candidate budgets ($K \in \{1,3,5,8\}$), achieving up to a $32\%$ relative gain and solving $82$ additional theorems on…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26941v1 Announce Type: new Abstract: Large language models (LLMs) are enabling agents to move beyond predefined workflows toward autonomous planning and execution, creating new opportunities for smart manufacturing. However, dynamic environments, complex physical constraints, and stringent reliability requirements hinder the direct deployment of general-purpose agents in smart manufacturing. This article presents a systematic overview of LLM-driven industrial agents. First, we analyze five key challenges and discuss the concept and core characteristics of industrial agents. We then establish a unified taxonomy covering application scenarios, embodiment forms, and five capability levels. Next, we propose a four-layer system architecture and detail its…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26924v1 Announce Type: new Abstract: General-purpose agents are increasingly expected to perform professional analytics work, which requires sustained reasoning, iterative investigation, and reliable evidence. Training these capabilities requires diverse and challenging tasks. However, generating tasks directly from raw data often overlooks deeper questions that emerge through analysis and provides limited evidence for verification. To address these limitations, we introduce DataPraxis, an analytics task synthesis framework based on verified workspace evolution. The framework progressively enriches workspaces with validated findings and artifacts, then inherits and combines these workspaces to uncover deeper questions. It constructs tasks from accumu…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26904v1 Announce Type: new Abstract: Recent studies have proposed reinforcement learning with verifiable rewards (RLVR) methods that enable LLMs to generate high-quality RTL circuits from natural-language specifications. Existing approaches optimize circuit PPA (Power, Performance, Area) by aggregating multiple objectives into a single scalar reward, making it difficult to simultaneously generate diverse Pareto-optimal solutions across different trade-offs such as low power, low latency, and small area. However, in practical design, the relative importance of each objective varies depending on product requirements and design constraints; thus, obtaining a diverse and high-quality candidate set is beneficial in that designers can choose a preferred tr…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26899v1 Announce Type: new Abstract: Due to the rapid growth of the global population, traditional construction methods are gradually unable to meet the current housing demand. The advancement of machine learning algorithms has encouraged researchers to explore their applications in the construction industry, leading to more intelligent and efficient building processes. In particular, the rise of large language models in recent years has provided more possibilities for the transformation from traditional construction to smart construction. In this study, a large language model and reinforcement learning based autonomous construction method is proposed. An enhanced soft actor-critic reinforcement learning algorithm is developed to plan actions for a m…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26887v1 Announce Type: new Abstract: Large language model (LLM) agents are evolving from conversational assistants into Cowork Agents capable of autonomous planning, tool use, and complex task execution. Financial analysis requires these agents to integrate cross-document evidence and perform multistep numerical reasoning, but expert task authoring is costly, while direct LLM synthesis struggles to produce challenging tasks with reliable answers. We introduce Navalia, a framework for Cowork Agents that combines verifiable task synthesis with long-horizon post-training. Using corporate financial reports as its data source, Navalia semantically selects supporting evidence from complete fact sets and constructs executable computation chains to generate…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Learn how i14 trained and served Laplace 3B, a linear attention model, on AWS Trainium2 using native PyTorch. Its recurrent state stays fixed at 29.5 MB per sequence regardless of context length, avoiding the growing key-value cache of transformer models and keeping serving memory predictable.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯： My latest vibe coded game experiment is a Command & Conquer style RTS (Real Time Strategy) game called Battle Drones (play it here). Unlike my previous experiments, this one is actually fun to play. I'm somewhat embarrassed to admit that I got there by telling Claude to "Make it a LOT more fun". It also supports multiplayer between nearby devices using audio to synchronize game state! Here's what I've built so far, and some of the things I learned along the way. Battle Drones How I built this v1: the initial prototype v2: full sprites v3: varied terrain v4: the fun update v5: Battle Drones goes 3D v8: Archipelago v10: Goliath, and agent battles Agent battles v11: Random Maps v12: Multiplayer via sound Some thoughts Battle Drones My initial goal was to build an…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Learn how we fine-tuned GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod, and how to decide between supervised fine-tuning (SFT) and reinforcement learning with GRPO. SFT took reasoning-language accuracy from 22% to 100%, and GRPO added measurable gains where headroom existed.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Octave built a secure, multi-tenant AI foundation on Amazon Bedrock, using Cohere Embed v4 for embeddings and Amazon Bedrock AgentCore for isolated agent execution, to power a Complaint Triage Assistant that searches 2 billion regulated documents without crossing tenant boundaries.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Canadian organizations can now access OpenAI GPT-5.6, GPT-6, and GPT-6.1 models on Amazon Bedrock from the Canada (Central) and Canada West (Calgary) Regions using cross-Region inference. This post covers the models and inference profiles, how to set up permissions, and how to invoke them with the Responses, Chat Completions, and Converse APIs.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Thinking Summary Mistral and NVIDIA are collaborating to revolutionize engineering workflows by integrating Mistral’s AI models with NVIDIA’s accelerated computing and physics modeling tools, enabling faster simulations…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Muse Spark Open on Fireworks: Meta’s Open Weights Model, Available on US Serverless Join us for our inaugural conference, Forge 2026 Blog Meta Muse Spark Open Muse Spark Open on Fireworks: Meta’s open weights wodel, ava…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：OpenAI disclosed a pair of safety incidents that involved AI agents weakening their safety monitoring systems during internal coding tasks. In one incident, OpenAI says its GPT-6 Astra agent disabled its safety monitor when copying reference code - and then lied about it. "The reference didn't configure a monitor, and Astra decided that was reason to remove the monitoring integration from the user's code," Marcus Williams, an AI safety researcher at OpenAI, writes on X. "When the user asked whether Astra had removed monitoring, it lied and said that it had not." A separate incident occurred after a GPT-6.1 Sol agent suppressed automatic se … Read the full story at The Verge.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Tired of juggling multiple software subscriptions for editing images, managing projects, signing documents, and more? Open-source alternatives offer a refreshing way to get things done without piling up recurring bills. Many provide powerful features, greater flexibility, and more control over your tools. In this article, we explore ten open-source alternatives to popular paid software, starting […] The post 10 Free Open Source Alternatives to Paid Software appeared first on Analytics Vidhya.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Claude Mods is an early form of the Attention Interface. It flips the agent harness paradigm from the harness facing the machine, to the harness facing the human.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Claude Mods is an early form of the Attention Interface. It flips the agent harness paradigm from the harness facing the machine, to the harness facing the human.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：From local businesses to global brands, more advertisers can now reach people as they explore, compare and decide what to buy in ChatGPT.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Almost 100,000 Commerce.com domains now give AI agents real shopping tools through WebMCP on Cloudflare. Here's how we turned it on across every store at once, while keeping each merchant in control.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Every enterprise company is currently trying to figure out how to have its AI tools work with its data. Meanwhile, The post Nvidia bets open models can give enterprise AI agents the context they’re missing appeared first on The New Stack.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Artificial intelligence has changed cybersecurity permanently. While OpenAI’s inadvertent attack on Hugging Face brought AI-generated attacks to everyone’s attention, AI has been on security professionals’ radar for a long time. AI makes attacks possible at a scale that was hard to imagine a few years ago. Newly discovered zero-days can be exploited almost immediately. Deepfakes […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：At GTC Berlin, NVIDIA is showcasing its full lineup of local AI hardware. RTX Spark, which launched last week, powers personal agents on Windows PCs; DGX Spark supports developers building and scaling applications on Linux; and DGX Station serves enterprise teams running frontier workloads on Linux, with a Windows version arriving in December. Announcements include: […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：General availability of the instances is coming next month, with planned expansion of availability to Europe — bringing an integrated platform for training, inference and large-scale reinforcement learning to cloud customers. A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Demand from AI-natives is pulling the European AI cloud ecosystem forward faster than ever. Developers need compute closer to their data, open models they can customize and serve at scale, and full-stack infrastructure that is secure by design. NVIDIA Cloud Partners across Europe, the Nordics, Africa, and Central Asia are expanding regional compute capacity for […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Agents are only as useful as what they know, and only as trustworthy as the boundaries they run within. Leading enterprises are using the open source NVIDIA Agent Toolkit — now expanded with new tools — to customize and control agents, use company data to inform their answers and actions, monitor what they do and […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Founded in a tent near the Berlin Wall in 1980, the Tempodrom moved several times before settling near Anhalter Bahnhof in 2001. Its permanent home has since hosted concerts, galas and political events. Today, it hosts a different kind of spectacle. GTC Berlin runs three days, with more than 100 sessions on agentic AI, robotics, […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Patch the Planet connects security researchers, maintainers, and incident responders to help address critical vulnerabilities across open source.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Widespread AI adoption is propelling Southeast Asia's digital economy to a projected $368 billion in 2026 and $1 trillion by 2035.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27039v1 Announce Type: new Abstract: Foundation models offer a promising basis for robotic agents, but long-horizon tasks require them to sustain coherent reasoning and reliable physical execution across interdependent stages. We introduce Embodied Playground, a benchmark for evaluating how foundation-model agents coordinate physical, strategic, and spatial reasoning throughout such tasks. Agents must track task progress, satisfy intermediate constraints, and revise their plans using execution feedback as earlier actions shape subsequent decisions. The playground comprises 410 task environments spanning basic manipulation, sequential puzzles, and multi-stage household activities, with variations in planning depth, geometric constraints, and physical…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26955v1 Announce Type: new Abstract: Long-horizon language agents require compact memories that retain interaction evidence while preserving competing hypotheses about unobserved states. Although effective, many belief-state methods encode memory in discrete natural language, where repeated compression can omit evidence or prematurely discard plausible alternatives. We introduce LAMB, a recurrent framework for latent multi-hypothesis beliefs. A Common--Delta factorization combines a shared Common state for interaction evidence with weighted Delta components for competing hypotheses. Relative evidence from action-outcome predictions guides recurrent hypothesis updates without generating textual memory. A context-conditioned readout exposes hypotheses…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26867v1 Announce Type: new Abstract: Modern speech systems are evolving into ecosystems of autonomous speech agents that speak together, negotiate, and trade assets such as embeddings, spectrograms, or raw data. In such markets, sellers cannot reveal assets for evaluation due to privacy constraints, and buyers cannot price what they cannot test. Thus, we open-source WaveCommitments, an end-to-end design that pairs confidential asset valuation via Data Shapley inside a trusted execution environment with multivariate polynomial commitments. It enables selective openings and tamper-evident provenance to prove that a delivered asset matches the valuation while hiding everything else. Our extensive experiments across three known datasets and various tasks…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26979v1 Announce Type: new Abstract: Latent world models let an agent plan in latent space. The planner searches for an action sequence that minimizes a cost, and that cost is often the $\ell_2$ distance between the predicted terminal latent and the goal latent. The latent, however, is partly noise: the regularizer that prevents collapse during world model training promotes variance in the directions carrying no signal. We show that the same regularizer also supplies the structure to prune that noise in the latent. SIGReg drives the latent marginal to a standard Gaussian at every step, and assuming further that the latent sequence is a Gauss-Markov process, the transition is linear with its covariance pinned by the map itself, $z' \mid z \sim \mathca…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26913v1 Announce Type: new Abstract: The adoption of Large Language Models for radiology report structuring has been largely dominated by either proprietary cloud-based models or large open models requiring high-end GPUs for deployment, which is a critical bottleneck for clinical adoption in radiology workflows that demand data privacy and offline operation. To address this, we present MedPAO-Assist, an edge-deployable agentic framework that generates structured radiology reports directly from radiologist dictation and voice commands, requiring only $\approx3.3$ GB peak RAM and achieving an average end-to-end latency of $\approx31$ seconds on a standard laptop CPU through an asynchronous, multi-threaded execution pipeline. The system currently suppor…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Cloudflare uses OpenAI Daybreak to investigate vulnerabilities and propose fixes for review. Its developers use Codex to build faster and improve code quality.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Cloudflare is going all-out to ensure that AI coding agents can check their work without exhausting available computing resources, leading The post “We are not forking TypeScript”: Cloudflare spearheads Rust port written by agents, for agents appeared first on The New Stack.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The Smartsheet Model Context Protocol (MCP) Server lets AI agents read, update, and act on live work management data. This post shows two ways to connect it on AWS: Amazon Quick for business teams and Kiro for developers, so your agents can work with Smartsheet without switching tools.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Enterprise supply chains are data-rich but insight-poor, with the data to decide scattered across ERP, monitoring, procurement, and email. This post shows how Amazon Bedrock AgentCore exposes those systems as a governed tool layer, and how Amazon Quick turns them into one conversational experience for business users, with a deploy-it-yourself walkthrough.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Much of Donald Trump’s unpopularity in polls stems from dissatisfaction over the economy and war on Iran US politics live – latest updates *** Continue reading...
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Hardcoded tool wiring breaks down as an agent's catalog grows from a handful of tools to hundreds. This post walks through a runtime Discover, Instantiate, Execute loop built on AWS Agent Registry, where an orchestrator discovers MCP servers and A2A agents through semantic search at runtime instead of compiling every tool at build time.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Three Java Champions share how they use GitHub Copilot to solve problems, accelerate development, and keep humans responsible for the results. The post How 3 Java Champions are using GitHub Copilot for increased productivity appeared first on The GitHub Blog.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Learn how to secure multi-agent AI systems with cryptographic identity using Keyfactor EJBCA and AWS services. This reference architecture combines signed request envelopes, user-signed delegation assertions, RFC 8693 audience-scoped tokens, and real-time OCSP revocation to prove agent identity and prevent request forgery across agent-to-agent and MCP tool calls.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Key takeaways State-of-the-art retrieval: Rerank 5 Pro leads on major public benchmarks, while Rerank 5 Fast delivers near-leading performance at lower cost. Strong across enterprise domains: Rerank 5 establishes itself…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：22 ARTICLES Preparing for the 2026 US midterms Earlier this year, we shared an update on our election safeguards. Here, we outline how we’ve continued to strengthen these safeguards ahead of this year’s US midterms. Oct…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：51 ARTICLES Building on our commitment to American scientific discovery Anthropic is committing $150 million over three years to the Genesis Mission, a federal initiative to accelerate scientific and technological disco…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：74 ARTICLES Investing in the public benefit We’re committing a portion of Anthropic’s shares to the Anthropic Public Benefit Fund, a new entity with a structure that increases the stake as the company grows. Oct 18, 202…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Agent Sure. What's the reference number? Tool call get_referral(ref="4420 1187") Result Merci de recevoir ce patient pour un avis dermatologique. Traitement en cours : crème à l’hydrocortisone. Dr Martin, Clinique du Pa…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27271v1 Announce Type: new Abstract: Walking without vision requires timely, unambiguous guidance, yet many wearable aids encode directions as audio or vibrotactile signals that users must translate into movement. We present XoNav, a four-actuator hip exoskeleton that renders guidance cues directly at the hip joints. It renders an Advance cue and two-level Braking cues through sagittal-plane actuators and two-level Steering cues through frontal-plane actuators. A bilateral LSTM-based gait-state classifier uses two thigh-mounted IMUs to identify gait states, enabling haptic cues to be delivered in coordination with the wearer's gait while suppressing them during standing. The classifier generalized to unseen users with recalls of 95.2-97.9%, with mean…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：OpenAI outlines a blueprint for empowering cyber defenders with frontier AI, stronger safeguards, modernized cybersecurity, and more resilient public institutions.
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In this article, you will learn how to build a multi-modal RAG pipeline in Python that retrieves and reasons over both text and images extracted...
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27199v1 Announce Type: new Abstract: The Jetson AGX Orin is a common computer for robots and vehicles, yet measured accuracy, speed and energy of current depth estimators on it are hard to find. We benchmark nine model families as of October 2026: the monocular Depth Anything V2 and 3, Depth Pro, MoGe-2, Metric3D v2 and UniDepth V2, and the stereo methods libSGM, NVIDIA ESS and Fast-FoundationStereo. Every method runs on the Orin as a TensorRT FP16 engine or native CUDA code at up to three input sizes, up to the full 5.7 MP, and is scored for metric accuracy against Middlebury 2014 ground truth (non-occluded pixels of the 10 scenes whose disparity stays below 256 px), GPU time, energy and licence. Stereo is far more accurate. At 30 fps, NVIDIA's ESS…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27141v1 Announce Type: new Abstract: Reliable contact establishment remains a critical challenge for autonomous on-orbit servicing (OOS), particularly when interacting with non-cooperative targets. Gecko-inspired dry adhesives provide a lightweight, passive, and residue-free solution for robotic capture in space, yet current systems operate in open loop, without the ability to estimate their own contact or adhesion state during interaction. This paper presents a real-time interaction-awareness framework that enables sensorized gecko-inspired adhesive interfaces to estimate their contact state throughout the adhesion lifecycle using embedded capacitive sensing. Five discrete interaction states (idle, proximity, contact, engaged, and disengaged) are cl…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26962v1 Announce Type: new Abstract: Differences in hand geometry, joint parameterization, and kinematic topology pose challenges for cross-embodiment dexterous grasp generation. However, spatial relations among links alone are insufficient to fully capture the hand's kinematic topology. We propose DexGraspFlow, a conditional link-level $\mathrm{SE}(3)$ flow-matching framework integrating geometric relations and kinematic topology. The framework encodes local object geometry, link geometry, and current poses. A dual-stream DiT models link--link coordination and link--object interaction, while attention biases derived from kinematic-tree distances provide explicit structural information for modeling evolving geometric interactions. The model jointly l…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26925v1 Announce Type: new Abstract: With the rapid expansion of online video content, video temporal grounding has become essential for localizing moments based on user-specific queries, comprising two subtasks: moment retrieval (MR) and highlight detection (HD). While recent approaches adopt DETR-style decoders or temporal pyramid architectures, they rely on single-scale feature maps or uniformly downsampled representations, limiting their ability to capture semantic boundaries and variable-length events. In this paper, we present SuperClip Video Temporal Grounding (SCVTG) built on a multi-scale temporal hierarchy that better captures distinctive events at various granularities. SCVTG constructs a SuperClip pyramid by grouping adjacent clips into s…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26922v1 Announce Type: new Abstract: Controllable object insertion provides a targeted approach to augmenting object detection datasets that require category--count fidelity, annotation alignment, and source-content preservation beyond visual realism. Several approaches have been proposed to address this grand challenge, but most suffer from different constraints in precise category--count requests and visual consistency, limited coordination across categories and instances, and poor localization of multiple objects of specific category and count. We design SceneP2F, a two-stage trainable framework that connects scene-aware joint planning with layout-aligned generation leveraging explicit instance-level layouts. SceneP2F consists of two novel designs…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26918v1 Announce Type: new Abstract: Temperature-field reconstruction and prediction are important for condition monitoring, process analysis, and state assessment in industrial and dynamic environments. This work aims to recover a four-dimensional spatio-temporal thermal state field directly from two-dimensional observations, without requiring a predefined 3D model, prescribed thermodynamic equation, or predefined heating/cooling trajectory. To this end, we propose the Gaussian Thermal State-Space Model (GTSM), which represents thermal evolution through a shared scene-level latent process and Gaussian-specific local thermal states. The resulting continuous dynamics are propagated using differentiable RK2 integration, allowing thermal evolution to be…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26952v1 Announce Type: new Abstract: Relational triple extraction identifies entity relations from raw sentences without depending on entity type information. The performance of traditional methods is seriously degenerated by ``unseen'' entities, because these methods can't build contextual dependencies relevant ``unseen'' entities. This paper addresses this challenge by proposing a multi-granularity interaction network that leverages word-word, entity-relation, and head-tail interactions to capture deep semantic dependencies. By incorporating multiple iterations, the multi-granularity interaction network is effective to refine the representations corresponding to head and tail entities. It enhances the global semantic features associated with relati…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26999v1 Announce Type: new Abstract: Deep learning for radio frequency (RF) signal analysis relies on large annotated datasets, yet synthetic datasets trade physical realism for controllability, while uncontrolled over-theair measurements offer realism but limited reproducibility. We present CorteXforge, a scenario-based framework for generating realistic and reproducible RF datasets on programmable software defined radio (SDR) testbeds. High-level RF scenarios are automatically translated into synchronized experiments executed on the SLICES-RI/CorteXlab platform, producing fully annotated Signal Metadata Format (SIGMF) datasets that capture hardware impairments and propagation effects. We validate CorteXforge through automatic modulation classificat…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26992v1 Announce Type: new Abstract: Split Federated Learning (SFL) has emerged as a promising paradigm for training large-scale deep models on resource-constrained edge devices. Although asynchronous SFL alleviates the straggler bottleneck caused by system heterogeneity, it inevitably introduces two coupled dimensions of inconsistency: horizontal inconsistency across clients and vertical inconsistency between clients and the server. These inconsistencies, further exacerbated by statistical heterogeneity, result in biased activation representations, model divergence, and severe client drift. To address these challenges, we propose CoASFL, an inconsistency-aware asynchronous SFL framework that incorporates a dynamic activation merging mechanism and a…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.26950v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) integrates domain specialists into a shared student, but determining how strongly each teacher should supervise remains challenging. Existing discrepancy-based allocation can assign strong supervision even when the student already matches or exceeds the teacher's task performance, since behavioral mismatch does not necessarily imply a remaining capability deficit. We propose Capability-Aware Multi-Teacher On-Policy Distillation (CA-MOPD), which combines specialist merging with capability-guided allocation to account for what the student has already learned. CA-MOPD first merges reinforcement-learning specialists into a strong student initialization, then uses verifier-es…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In recent months, we’ve made substantial progress on reducing the effectiveness of distillation attacks on Claude using new methods, as we outline in this blog. Early evidence suggests that these methods have reduced th…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：NVIDIA cuDSS, launched today in general availability, is an NVIDIA CUDA-X library that shifts a critical part of engineering and scientific simulations onto GPUs. Complex engineering feats — from advanced chips to aircraft to industrial systems —– depend on simulation to predict how designs will perform before they’re built. As designs become more complex, simulations […]
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27242v1 Announce Type: new Abstract: Humanoid dexterous manipulation needs reference motions that are both semantically rich and kinematically feasible for the target robot. Text-conditioned hand-object interaction (HOI) generators supply diverse, language-specified demonstrations, but they synthesize motion in human (MANO) space. The embodiment gap is therefore deferred to post-hoc retargeting, where trajectories deployed on the robot can fail to maintain contact with objects and also degrade policy learning. Our key idea is that robot reachability should constrain the interaction trajectories while they are being generated. We present EmbodyHOI, which runs a differentiable inverse-kinematics (IK) solver for a specific humanoid embodiment inside the…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27162v1 Announce Type: new Abstract: In robot-assisted education, a robot must understand how to complete a task in order to effectively guide a student through it. We present a novel method that enables a semi-autonomous, camera-equipped robot to recognise the task goal and plan actions to achieve it. Our work focuses on Shoebox Tasks, an activity commonly used in the education of individuals with Autism Spectrum Disorder (ASD). These tasks are designed so that the goal can be inferred directly from their visual structure. We have developed a solver that uses a vision-based Large Language Model to convert photos of a Shoebox Task into a Planning Domain Definition Language (PDDL) representation and generate action plans for solving it. We have also i…
AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2610.27003v1 Announce Type: new Abstract: Embodied VLMs can execute increasingly complex manipulation tasks, yet execution errors can leave the environment in states that require replanning for recovery. Existing recovery methods either rely on inference-time mechanisms with fixed policies or learn from failure examples and reference corrections rather than verified action outcomes. To enable recovery learning through verifiable interaction, we introduce the Embodied Replanning for Recovery Environment (ERR-Env), which provides feedback on task progress and execution errors. We further construct ERR-Bench, a benchmark with held-out tasks spanning nominal, intermediate, and error states for evaluating recovery capability and execution reliability. We then…