AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：We can't find the internet Attempting to reconnect Something went wrong! Hang in there while we get back on track AI Can Make You Suck Faster Too By Jordan Andersen on 17/08/26 Not too long ago, I shared a post that I r…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Celeris-1 Magnus: the fastest model for agentic use cases CELERIS-1 MAGNUS The fastest model for agentic work. Magnus is built for agents that need to think, use tools, and get things done, without waiting around. Get a…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Thanks for trying Clippy Vision! If you've installed and used it (even briefly), we'd love your honest feedback. It takes about 5 minutes and directly shapes what we build next. **Feedback form:** https://forms.gle/qxqm…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：You can now create decent video faster than you watch it. This is the start of... something. We’re not sure what.

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AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Back to Blog The Problem Modern AI work already spans multiple tools. You might research in Gemini, think things through in ChatGPT, build in Claude Code or Cursor, and keep follow-up discussions going across all of the…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Mathematics New submissions Cross-lists Replacements See recent articles Showing new listings for Tuesday, 1 September 2026 Total of 1082 entries Showing up to 2000 entries per page: fewer | more | all New submissions (…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Notifications You must be signed in to change notification settings Fork 1 Star 3 BranchesTags Open more actions menu Latest commit History 10 Commits 10 Commits Folders and files NameName Last commit message Last commi…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：An EU export ban on Dutch tech giant ASML’s machines could force the pause we all need At this point, it should be clear that AI is a choose-your-own-adventure book where every option ends in disaster. Exploding carbon emissions and ecological collapse? Turn to page 37. Other outcomes include some or all of: the bubble bursting and an ensuing financial crisis; mass unemployment via automation; the end of democracy and the rise of authoritarian surveillance states; raving cults who believe the pattern-matching algorithm is a consciousness; terrorists who create devastating bioweapons; nation states that deploy autonomous weapons systems that act on non-human timeframes; nation states or terrorists that hack all the myriad systems we depend on; or an AI that, con…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：We are used to the idea that our fellow humans might intentionally mislead or manipulate us, but the idea that machines can now do the same is deeply unsettling. Researchers are racing to find solutions before it’s too late The summer issue of the Long Read magazine is out now. Click here to order In November 2023 – a lifetime ago in the field of artificial intelligence – some of the most powerful people in the world descended on Bletchley Park, the wartime codebreaking hub in Buckinghamshire, to talk about AI safety. In attendance were the then US vice-president, Kamala Harris, the AI bosses Sam Altman and Dario Amodei, delegations from 28 countries, two of the three so-called “godfathers” of AI, and Elon Musk. The first iteration of ChatGPT had been released…

該論文將Park-Ravani樣條構造從SO(3)推廣到正交對偶張量羣，用於剛體位移的插值。藉助指數映射右雅可比的對偶擴展，所得曲線不僅滿足位姿插值與物體對偶旋量及其一階導數的連續性，還進一步證明物理加速度場連續。作者區分了代數對偶轉移與時間微分延拓，並利用對偶對數座標中的三次或五次Hermite插值修復了一階完整缺陷。

研究人員提出針對自動駕駛汽車相機-激光雷達在線校準系統的首個物理攻擊方法ACA。攻擊者僅用一張對抗性海報，就能先騙過失準檢測器、再操縱校準估計器，使車輛接受錯誤的傳感器變換參數。在KITTI/nuScenes、CARLA模擬器及真實Husky機器人上，ACA造成顯著旋轉誤差、嚴重損害目標檢測，並可在模擬場景中引發碰撞。

一篇新論文提出統一的基於自迴歸擴散的圖生成模型，可從觀測到的垂直平面自下而上地構建完整3D場景圖（3DSG），並聯合學習圖結構與空間特徵，適用於任意層級深度。實驗顯示，該方法在合成場景、真實建築平面圖和機器人傳感器數據上優於所有學習和隨機基線，在最大層級及真實單層數據上還優於具備目標圖規模先驗的一次性模型。研究還提出基於Fused Gromov-Wasserstein距離的圖級評估方法。

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28723v1 Announce Type: new Abstract: Automated drift controllers commonly track a prescribed drift equilibrium, sideslip reference, or trajectory. These formulations establish how to execute drift, whereas the continuous transition from grip driving to drift near the handling limit remains unresolved. This paper defines drift emergence in a repetitive lap time minimization task, where neither the controller objective nor the reward contains an explicit drift reference. A boundary exploration learning model predictive controller (BE-LMPC) constructs an empirical safe set and a locally shifted terminal cost from completed laps. By iteratively improving spatial speed allocation under a fixed global speed bound, the controller progressively explores larg…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28718v1 Announce Type: new Abstract: Video world models increasingly serve as data engines, action planners, and simulators for embodied AI, but conventional embodied world model (EWM) benchmarks lack a unified 3D-grounded protocol for establishing whether generated rollouts preserve the underlying 3D scene state or translate into executable actions. We introduce RoboPhys-3D, a 3D-grounded EWM benchmark built on RoboTwin 2.0, covering 50 manipulation tasks across four regimes, with 5,000 episodes and 25,000 multi-view ground-truth videos. A defining feature of RoboPhys-3D is that generated and ground-truth videos are processed through the same 3D reconstruction pipeline, enabling reconstruction-induced error to be distinguished from generation-induce…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28697v1 Announce Type: new Abstract: Additive manufacturing (AM) enables compact hydraulic components whose internal fluid channels can follow free-form 3D paths rather than conventionally drilled holes. A representative case is multi-group channel layout in rotary direct-drive servo valves: once a channel is placed it permanently occupies volume, so later channels must clear earlier geometry--unlike classical multi-agent pathfinding (MAPF), where agents free space after moving. We study this setting as multi-group pipe routing under permanent geometric occupancy. Our contributions are a problem formalization with geometric dual-witness conflicts, a constructive 3D benchmark (two corridor generators x two obstacle painters, controlled difficulty, fea…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28693v1 Announce Type: new Abstract: Enabling humanoid robots to respond to human speech with synchronized and semantically meaningful gestures is fundamental to natural human-robot interaction. However, this task faces three critical barriers: the scarcity of semantically rich datasets, the "modality eclipse" where models ignore audio cues in favor of kinematic inertia, and the sim-to-real gap regarding physical safety. We propose RoboGesture, a robot-centric framework that co-designs data, modeling, and control to power a complete interactive human-humanoid system in which the robot listens, responds, and gestures in real time. We first establish the RoboGesture dataset featuring over 300 gesture categories and develop an automated pipeline to synt…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28677v1 Announce Type: new Abstract: This paper presents \ul{CogRun}, a framework that enables safety-critical ground robots to perform cognitively-grounded runtime learning entirely on edge-AI devices in unknown physical environments, without prior maps or perceptual knowledge. CogRun consists of three components: a Learning-Agent, a Rational-Agent, and a Coordinator. The Learning-Agent is novel in cognitive-neural learning architecture, which featurs dedicated replay buffers, cognition-driven experience sampling, and a safety-aware action blending of actor-critic reinforcement learning (RL) with instance-based learning (IBL). The Rational-Agent is a non-learning module that complements the Learning-Agent by exclusively handling safety-critical func…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28664v1 Announce Type: new Abstract: Despite the success of foundation models in language and vision, their expansion into embodied AI is bottlenecked by a lack of generalized touch sensing. This limitation is especially relevant to consumer electronics, where smartphones, wearables, VR controllers, home robots, and health monitoring devices require safe and adaptive physical interaction. Constrained by hardware heterogeneity and the necessity of active physical data collection, current haptic models remain rigidly task-specific. To overcome these limitations, this article explores the transformative potential and developmental trajectory of Haptic Foundation Models (HFMs). We detail the paradigm shift required to transition from passive Large Langua…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28656v1 Announce Type: new Abstract: Behavior-cloned Vision-Language-Action (VLA) driving policies struggle with rare rule-governed maneuvers at signalized intersections. Braking and launching examples contribute little to averaged trajectory loss, while fused representations lack explicit supervision for the governing traffic-light and stop-line state. We present RedLight-VLA, a training objective that uses expert futures and automatically generated perception targets without additional manual rule annotation. First, trajectory-derived behavioral reweighting (BR) emphasizes rare deceleration and acceleration using rotation-invariant longitudinal dynamics and a scale-preserving reduction that exactly recovers the baseline when disabled. Second, paral…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28675v1 Announce Type: new Abstract: Video reasoning tasks such as grounded video question answering and temporal grounding require selecting temporal evidence that supports the query. In many current training setups, temporal supervision is applied through local objectives such as boundary regression or span generation, while verification is used mainly to rerank candidate segments at inference time. We study whether a frozen verifier can also guide training. Our multi-agent framework couples a trainable \emph{Grounder} with a frozen \emph{Verifier}: the Grounder samples candidate trajectories and evidence segments, the Verifier assigns query-conditioned segment scores, a group-relative policy-gradient objective favors trajectories that outperform t…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28674v1 Announce Type: new Abstract: Multi-exposure is an efficient way to capture real-world high-dynamic-range (HDR) scenes. However, HDR imaging suffers from severe ghosting artifacts in dynamic scenes due to the temporal gap between sequential exposures. In this article, we categorize the literature on two important topics on HDR imaging: multi-exposure fusion (MEF) and ghost removal. Conventional filter-based and data-driven methods are studied in pixel space and feature space. For popular deep learning-based approaches, we provide a granular taxonomy based on their alignment and fusion domains: pixel-space methods, which typically employ explicit motion compensation such as optical flow or spatial transformers, and feature-space methods, which…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28673v1 Announce Type: new Abstract: Deploying vision perception models in autonomous vehicles requires that we prioritize inference speeds, resulting in a model with shallower architectures and lesser model parameters (i.e., more pruned). Such small models do not generalize well, which could result in poor performance when encountered with novel scenarios. We propose a system that overcomes this by continuously retraining the vision models on the cloud with data uploaded by vehicles. We leverage the abundant compute resources, including machine learning accelerators, of the cloud to run a highly-accurate oracle model that will guide the retraining process of the on-vehicle model. This newly trained model is transmitted to the vehicle over the networ…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28672v1 Announce Type: new Abstract: Autonomous vehicles operate in dynamic, ever-changing environments where new scenarios and edge cases constantly emerge. As a result, static learning models are inadequate for ensuring safe and reliable operation. Continuous learning is essential for adapting to these evolving conditions and maintaining robust performance across diverse real-world settings. However, autonomous vehicles generate massive streams of visual data during operation, and existing continuous learning approaches typically rely on heuristic sampling methods that fail to capture temporal dynamics, often overlooking critical learning opportunities or selecting redundant frames. In this paper, we introduce FrameScope, a temporal data valuation…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28671v1 Announce Type: new Abstract: AI-generated art has sparked debates around potential plagiarism, as these images may closely resemble existing artworks. This research quantifies the similarity between original pieces and AI-generated counterparts, particularly those produced by the Stable Diffusion XL Refiner 1.0. We use Siamese Networks with frozen CLIP encoders and cosine similarity optimized through triplet loss. A dataset of paired original and generated images was built using image-to-image generation and custom prompts, enriched with semantic descriptors and BLIP-2 captions. Prior studies report up to 81\% style replication and 90\% visual similarity. Our results show high discriminative performance: training accuracy reached 99.9\%, and…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28670v1 Announce Type: new Abstract: Diffusion Transformers achieve high-fidelity image and video generation, but their iterative sampling remains expensive, for each denoising step requires large matrix operations. Existing cache-based acceleration reduces redundant computation yet increases the VRAM footprint by storing intermediate states, which can directly constrain inference batch size. In this work, we propose a training-free acceleration method that performs stepwise forecasting for DiT sampling using a Barycentric Extrapolator. By leveraging barycentric extrapolation, our predictor is numerically stable and alleviates oscillatory artifacts analogous to the Runge phenomenon during forward forecasting. Across extensive experiments on both imag…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28669v1 Announce Type: new Abstract: Recovering an executable parametric CAD program from an observed object is fundamentally ambiguous, because the same final geometry can result from different construction procedures. We study this problem from four types of input: natural-language descriptions, rendered images, point clouds, and STEP/B-Rep geometry. MIRAGE-CAD maps each input to a shared construction representation and mediates program generation through an explicit construction-plan interface. The resulting Python CAD code is executed by an OpenCASCADE kernel to build the solid and export it as STEP. On 2,500 held-out queries per modality, the system achieves 55.4-70.0% build success and 52.3-66.2% STEP export success without retrieval at inferen…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28666v1 Announce Type: new Abstract: Video-language models (VLMs) remain brittle on tasks that require tracking events over time and grounding answers in specific spatial regions. We propose that part of this limitation can be addressed through better organization of visual evidence at inference time. We introduce structured video prompting, a training-free inference-time method that augments the input video with lightweight spatial structure and temporal structure, providing explicit anchors for organizing evidence across space and time without changing model weights or decoding and without altering the question prompt in the main comparison. We evaluate this approach on two complementary video benchmarks and two open video-language models. Across t…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28665v1 Announce Type: new Abstract: Recent open-vocabulary segmentation models have advanced semantic perception for UAVs, but predictions from moving aerial platforms can remain temporally inconsistent across repeated observations of the same physical scene. We investigate temporal semantic stability by associating frame-wise predictions with persistent world-space locations through metric 3D fusion. We introduce a voxel-level evaluation framework that jointly characterises final semantic agreement, Semantic Belief Drift (SBD), Observation Persistence (OP), and semantic uncertainty. Experiments on UAVid-3D reveal substantial frame-wise semantic flicker and show that high aggregate world-space agreement can overstate temporal stability when location…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.28663v1 Announce Type: new Abstract: Reliable individual cattle identification supports disease surveillance, vaccination records, breeding management, and livestock insurance. Although the bovine muzzle provides a stable, non-contact biometric, existing muzzle-recognition systems largely assume a closed set of enrolled animals, limiting their practical deployment. We reformulate cattle muzzle biometrics as an open-set, gallery-based identification problem that can reject previously unseen animals and support incremental enrollment without model retraining. We introduce a leakage-controlled evaluation protocol based on identity-disjoint splits, per-fold retraining, held-out threshold calibration, verified duplicate removal, and bootstrap confidence i…