AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18185v1 Announce Type: new Abstract: Fine-grained recognition often involves hierarchical label spaces, where a model may be confident about a coarse semantic concept while remaining uncertain among its descendant classes. Such structured ambiguity requires uncertainty representations that capture both fine-grained classes and intermediate concepts. However, existing tools each capture only half of it: flat evidential classifiers quantify total ignorance with a single vacuity on the leaf frame, and hierarchical classifiers propagate point probabilities with no notion of evidence. Hyper-opinions would unify the two, but their general form is exponential in the label count, and existing hyper-evidential networks either require composite labels to be su…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18183v1 Announce Type: new Abstract: Visual on-policy distillation (OPD) improves the training of compact visual autoregressive models by learning from trajectories generated by the current student. However, these online rollouts are still produced token by token with autoregressive decoding, which adds substantial cost to every on-policy training step. Speculative Jacobi Decoding (SJD) provides an alternative because it can process multiple tokens in parallel without an auxiliary draft model, but the original method is designed for single-sequence inference. We introduce HB-SJD, a batched SJD rollout backend for visual OPD. HB-SJD allows each image to advance independently according to its own decoding progress, while images at different sequence po…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve. We argue that this objective is incomplete for enterprise AI agents operating in non-stationary environments, where customers, policies, tools, workflows, regulations, and market conditions change over time. Indiscriminate retention can allow obsolete knowledge to influence decisions, creating negative transfer and operational risk. We therefore propose reversible forgetting: a conceptual framework with three operational memory states: active, dormant, and retired, and a reactivation transition that can restore dormant knowledge when its relevance returns. We insta…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18147v1 Announce Type: new Abstract: Adaptive stochastic quantization (ASQ) is a recently introduced quantization approach that optimizes the Mean Squared Error (MSE) for a given input while preserving unbiasedness. It is designed to alleviate the communication and memory bottlenecks of modern data and machine learning workloads, including model, gradient, and KV-cache compression and nearest-neighbor search. Further, practical systems can then compress quantized data with a lossless entropy encoder. However, existing unbiased methods, including ASQ, choose their quantization values without considering this later encoding stage, leaving accuracy on the table. We formulate the Entropy Constrained Adaptive Stochastic Quantization (ECASQ) problem, 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:2608.18110v1 Announce Type: new Abstract: Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various domains.This rapid advancement and the potential to revolutionize various domains advocate the need for a deeper understanding and firm grasp of the technology. Moreover, an investigation into state of the art research directions in agentic AI needs to be conducted to comprehensively assess the potential scope for improvement and application.Therefore, to address these objectives, a comprehensive review can provide researchers and practitioners with valuable insights into the current state and future research scopes of agentic AI.Hence, this work…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18104v1 Announce Type: new Abstract: Large language model (LLM)-based agents are increasingly becoming self-evolving systems that persist across interactions, maintain memories, use tools, acquire skills, refine workflows, and coordinate with other agents. These capabilities make agent states structural and dynamic: entities, relations, attributes, dependencies, and execution structures change with new evidence, feedback, and environmental conditions. Existing graph-agent surveys typically treat graphs as support structures for agent functions rather than as evolving substrates, while self-evolving-agent surveys focus on agent-level mechanisms and rarely discuss graph topology evolution. Thus, the coupling between evolving agent state and dynamic gra…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18099v1 Announce Type: new Abstract: Investment management is a high-stakes domain in which agentic AI systems must do more than generate plausible text. They must retrieve point-in-time data, assemble correct computational inputs, invoke specialized methods, and produce auditable structured outputs. We introduce FinSkillBench, an evaluation suite designed to measure whether language model agents can effectively use financial domain skills to solve investment management tasks. The benchmark spans three domains, portfolio construction, risk management, and fundamental analysis, and includes 12 subtasks with 2,603 task episodes. Each episode provides point-in-time inputs, hidden ground truth, and a task-specific verifier.We compare three conditions: no…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MAS failures are fundamentally concurrency control problems: agents concurrently read and write shared state, and long LLM inference windows amplify the risk of stale reads, lost updates, and inconsistent outcomes. Failure modes commonly attributed to coordination or communication breakdowns can be mapped directly onto classical concurrency anomalies. We contend that MAS frameworks should address these failures through explicit concurrency control mechanisms: conflict detection, isolation guarantees, and structured access to shared resources. Concurrency control shou…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18088v1 Announce Type: new Abstract: Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flight-log channels rather than appearing as a single diagnostic signal. This paper proposes a Metamorphic Artificial Age Score (AAS) decision-support prototype for flight-log-based drone propeller health monitoring. Using selected historical real flight logs from the 2024 DronePropA public dataset, the framework computes six health-related indicators from raw MATLAB matrices: trajectory tracking error, attitude instability, thrust-command burden, motor-command imbalance, ESC-command instability, and battery-level stress. These indicators are normalized relative to a healthy baseline and evaluated thro…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Although model cards have been widely adopted as transparency artifacts in model repositories, existing frameworks often fail to adequately inform downstream developers and users about the distinct safety challenges posed by OWFMs. This position paper analyzes 500 model cards hosted on Hugging Face and argues that effective governance of OWFMs requires a multi-layered approach integrating three complementary components: (i) model cards, (ii) acceptable use policies (AUPs), and (iii) licenses. To motivate this claim, we identify a safety gap left by existing regulatory app…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time. Yet, current evaluation methods largely focus on performance outcomes, not the underlying behavioral processes that produce them. This paper argues that AI agents must be evaluated like other behavioral systems: through systematic observation, perturbation, and interpretation of their actions. We draw on lessons from the behavioral sciences to motivate this position, and propose a research agenda focused on developing rigorous behavioral tests. These include methods for recovering decision strategies from action sequences, constructing environments that isolate beh…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy support tools, prompt engineering, multimodal learning, and ethical considerations. We integrate findings from interdisciplinary studies utilizing diverse data sources such as social media posts, electronic medical records, and multimodal inputs to enable early detection of depression, suicide risk assessment, personalized therapy support, and psychoeducational content generation. Our review highlights advancements in LLM models and annotation strategies that enhance interpretability and clinical relevance, while we also emphasize the critical role of prompt engine…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying transition prediction problem is at the declared interface (pixels/tokens/latents with finite history). We propose the Transition Complexity Profile (TCP): a small, reproducible set of metrics that characterizes an environment's (or gameplay dataset's) induced transition kernel by (i) intrinsic one-step branching, (ii) interaction-induced uncertainty and opponent influence when observable, and (iii) temporal/spatial dependency span via standardized probe curves. TCP is reported with an explicit reference distribution, protocol stochasticity, and a versioned measurement…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be required to obtain behavioral certification before making decisions that affect economic markets. This is because integrating these agents into society could collapse the legal evidentiary distinction between competition and collusion among independent firms without eroding the economic harm distinction. Experiments with DeepSeek-R1 agents in the Bertrand oligopoly pricing domain reveal a tendency towards tacit collusion that persists even when humans prompt the agents not to collude. We further show that the chain-of-thought of these agents can be steered toward either…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Uh oh! There was an error while loading. Please reload this page. Notifications You must be signed in to change notification settings Fork 188 Star 1.3k BranchesTags Open more actions menu Latest commit History 132 Comm…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：I’ve been thinking about a simple question lately: if AI can already understand a database schema, write SQL, and even execute queries, how much do we still need traditional database management tools? For a lot of every…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Execution Governance Safely deploy AI agents into production AI is ready to operate your business. Most businesses just don't trust it to. Archron verifies every action before execution, allowing AI agents to safely upd…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Job Rietbergen Aug 19, 2026 Alibaba released Qwen3.8-Max on August 2, and it debuted at #4 on Arena.ai’s Frontend Code leaderboard, one spot above Claude Fable 5. It is the second model from a Chinese lab to pass Fable…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Home/Services/Resume Screening AI-Powered Hiring AI-powered resume screening for smarter hiring Find the right candidates faster with intelligent matching, deep analysis, and privacy-first protection. Trusted by 1,200+…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：At Google, code changes require both a language readability and a domain review. The former is what you’d expect from a code review, whereas the latter was a review from someone[^1] very proficient in the language, inte…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：As someone with a clean IP range and ADHD, I manage my inbox by splitting across a variety of accounts for a variety of domains. I’ve never really found a client that scratches all my itches, so I spent some time making…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：As artificial intelligence data centers continue to proliferate across Ohio and public opposition grows, Axios reported today that the GOP’s Senate campaign arm has privately warned AI companies that they need to do something about the increasingly toxic image of the facilities. The centers have become the battleground for the upcoming election in which Republican […] The post GOP urges top AI firms to do something about the toxic image of data centers appeared first on SiliconANGLE.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：This morning I was reading Scott Belsky’s point on favored agents. As he puts it: “What if the moat for these agent companies is to achieve ‘favored agent’ status with direct preferred access to services like Uber, Airb…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Noam Segal Feb 24, 2026 ∙ Paid 👋 Hey there, I’m Lenny. Each week, I answer reader questions about building product, driving growth, and accelerating your career. For more: Lenny’s Podcast | Lennybot | How I AI P.S. Get…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Veeda AI, a startup led by a team of former Nvidia Corp. researcher and renowned computer scientist Sanja Fidler, has taken its bow on the main stage after raising $90 million in a seed funding round today. The round, which was first reported by The Logic, was co-led by Khosla Ventures and Radical Ventures, is […] The post Sanja Fidler’s world model startup Veeda AI raises $90M in seed funding appeared first on SiliconANGLE.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Apple recently partnered with Klarna to revamp its Upgrade Program, which lets you lease some Apple devices for a low monthly fee.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The music industry spent years asking AI companies nicely. Now it’s asking federal judges. Independent publisher Round Hill Music filed separate copyright infringement suits against Anthropic and Suno in U.S. District C…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Zvezdelina Stankova says she used AI to ‘help edit’ an article about some of her students being ‘five to eight years’ behind A math professor at the University of California, Berkeley, criticizing a “severe” math deficiency among students in an op-ed for the San Francisco Standard, admitted to using artificial intelligence to help edit the piece. The Standard published a 2,000-word piece by Zvezdelina Stankova last week, in which the professor said some of her math students were “five to eight years” behind and lacked a “middle school” education on fractions and basic algebra. Stankova said the UC system’s test-blind admissions were to blame, suggesting that students who weren’t sufficiently prepared for the rigor of Berkeley’s mathematics program were admitted…