「langchain-core==1.4.0」 (langchain-releases) の agent-fw 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
Changes since langchain-core==0.3.86 chore(infra): merge v1.4 into master ( #37350 ) chore: bump urllib3 from 2.6.3 to 2.7.0 in /libs/core ( #37329 ) fix(core): avoid eager pydantic.v1 import in @depr
過去日のカウントは保持ポリシー（per-source cap / half-life）により縮む場合があります。直近 1〜2 日の活動量の目安としてご覧ください。 Past-day counts may shrink over time due to retention (per-source cap / half-life). Use this chart as a rough gauge of the last 1-2 days.
| Date | Count |
|---|---|
| 2026-05-09 | 5 |
| 2026-05-10 | 7 |
| 2026-05-11 | 38 |
| 2026-05-12 | 48 |
| 2026-05-13 | 84 |
| 2026-05-14 | 319 |
| 2026-05-15 | 96 |
AI要約 「Introducing Claude Opus 4.7」 (anthropic-news) の claude 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN Our latest model, Claude Opus 4.7, is now generally available. Opus 4.7 is a notable improvement on Opus 4.6 in advanced software engineering, with particular gains on the most difficult tasks. Users
AI要約 「Introducing Claude Design by Anthropic Labs」 (anthropic-news) の claude 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN Today, we’re launching Claude Design, a new Anthropic Labs product that lets you collaborate with Claude to create polished visual work like designs, prototypes, slides, one-pagers, and more. Claude D
AI要約 「Test of Time: Rethinking Temporal Signal of Benchmark Contamination」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2509.00072v4 Announce Type: replace Abstract: Post-cutoff performance decay of LLMs has been widely interpreted as a temporal signal for benchmark contamination, where public information release
AI要約 「Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12620v1 Announce Type: new Abstract: Building generalist embodied agents capable of solving complex real-world tasks remains a fundamental challenge in AI. Multimodal Large Language Models
AI要約 「Macro-Action Based Multi-Agent Instruction Following through Value Cancellation」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12655v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) in real-world use cases may need to adapt to external natural language instructions that interrupt ongoing beh
AI要約 「Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12673v1 Announce Type: new Abstract: Agent benchmarks have become the de facto measure of frontier AI competence, guiding model selection, investment, and deployment. However, reward hackin
AI要約 「Revealing Interpretable Failure Modes of VLMs」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12674v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly used in safety-critical applications because of their broad reasoning capabilities and ability to general
og AI要約 「Learning Transferable Latent User Preferences for Human-Aligned Decision Making」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12682v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as reasoning modules in many applications. While they are efficient in certain tasks, LLMs often stru
og AI要約 「On the Size Complexity and Decidability of First-Order Progression」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12691v1 Announce Type: new Abstract: Progression, the task of updating a knowledge base to reflect action effects, generally requires second-order logic. Identifying first-order special cas
og AI要約 「DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12702v1 Announce Type: new Abstract: General-purpose safety benchmarks for large language models do not adequately evaluate disability-related harms. We introduce DisaBench: a taxonomy of t
og AI要約 「CHAL: Council of Hierarchical Agentic Language」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12718v1 Announce Type: new Abstract: Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structu
og AI要約 「BEHAVE: A Hybrid AI Framework for Real-Time Modeling of Collective Human Dynamics」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12730v1 Announce Type: new Abstract: Existing AI systems for modeling human behavior operate at the level of individuals or detect events after they occur. As a result, they systematically
og AI要約 「State-Centric Decision Process」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12755v1 Announce Type: new Abstract: Language environments such as web browsers, code terminals, and interactive simulations emit raw text rather than states, and provide none of the runtim
og AI要約 「PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model
og AI要約 「Multimodal Hidden Markov Models for Persistent Emotional State Tracking」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12838v1 Announce Type: new Abstract: Tracking an interpretable emotional arc of a conversation via the sentiment of individual utterances processed as a whole is central to both understandi
og AI要約 「Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12856v2 Announce Type: new Abstract: The emergence of multi-agent systems introduces novel moderation challenges that extend beyond content filtering. Agents with malicious intent may contr
og AI要約 「Beyond Cooperative Simulators: Generating Realistic User Personas for Robust Evaluation of LLM Agents」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12894v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in settings where they interact with a wide variety of people, including users who are uncle
og AI要約 「When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12922v1 Announce Type: new Abstract: Large language models can follow complex instructions in a single turn, yet over long multi-turn interactions they often lose the thread of instructions
og AI要約 「Sustaining AI safety: Control-theoretic external impossibility, intrinsic necessity, and structural requirements」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本…
EN arXiv:2605.12963v1 Announce Type: new Abstract: As AI systems become increasingly capable, safety strategies must be evaluated not only by how much they reduce present risk, but by whether they could
og AI要約 「Position: Agentic AI System Is a Foreseeable Pathway to AGI」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12966v1 Announce Type: new Abstract: Is monolithic scaling the only path to AGI? This paper challenges the dogma that purely scaling a single model is sufficient to achieve Artificial Gener
og AI要約 「Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12975v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on m
og AI要約 「Useful Memories Become Faulty When Continuously Updated by LLMs」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12978v1 Announce Type: new Abstract: Learning from past experience benefits from two complementary forms of memory: episodic traces -- raw trajectories of what happened -- and consolidated
og AI要約 「Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.12988v1 Announce Type: new Abstract: Students learning algorithms often need support as they interpret traces, debug reasoning errors, and apply procedures across unfamiliar problem instanc
og AI要約 「MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13037v1 Announce Type: new Abstract: Current interactive LLM agents rely on goal-conditioned stepwise planning, where environmental understanding is acquired reactively during execution rat
og AI要約 「An Agentic LLM-Based Framework for Population-Scale Mental Health Screening」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13046v1 Announce Type: new Abstract: Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from ele
og AI要約 「GRACE: Gradient-aligned Reasoning Data Curation for Efficient Post-training」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13130v1 Announce Type: new Abstract: Existing reasoning data curation pipelines score whole samples, treating every intermediate step as equally valuable. In reality, steps within a trace c
og AI要約 「A Constraint Programming Approach for $n$-Day Lookahead Playoff Clinching」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13142v1 Announce Type: new Abstract: In professional sports, a team has clinched the playoffs if they are guaranteed a postseason spot, regardless of the outcomes of any remaining games. As
og AI要約 「Strikingness-Aware Evaluation for Temporal Knowledge Graph Reasoning」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13153v1 Announce Type: new Abstract: Temporal Knowledge Graph Reasoning (TKGR) aims at inferring missing (especially future) events from historical data. Current evaluation in TKGR uniforml
og AI要約 「Formal Conjectures: An Open and Evolving Benchmark for Verified Discovery in Mathematics」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13171v1 Announce Type: new Abstract: As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their cap
og AI要約 「Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning」 (arxiv-cs-ai) の research 関連アップデート。AI 要約が未生成のため、後続の Worker run で本文が補完されます。
EN arXiv:2605.13213v1 Announce Type: new Abstract: Multi-modal multi-agent systems (MM-MAS) have gained increasing attention for their capacity to enable complex reasoning and coordination across diverse
og