「Zed Editor Releases v1.2.5」 (zed-releases) の vscode 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。
Bump to 1.2.5 for @rtfeldman
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 | 320 |
| 2026-05-15 | 202 |
AI要約 概要 GitHub Copilot App のテクニカルプレビューが公開されました。 「GitHubと、VS CodeなどのIDEの間をつなぐツール」として、かなり便利だと感じました。全機能の紹介は他に記事がたくさんあると思うのでそちらに譲
og AI要約 「Zed Editor Releases v1.2.5」 (zed-releases) の vscode 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 Bump to 1.2.5 for @rtfeldman
media AI要約 「Zed Editor Releases v1.3.2-pre」 (zed-releases) の vscode 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 Bump to 1.3.2 for @rtfeldman
media AI要約 「Merging Methods for Multilingual Knowledge Editing for Large Language Models: An Empirical Odyssey」 (arxiv-cs-cl) 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:2605.13919v1 Announce Type: new Abstract: Multilingual knowledge editing (MKE) remains challenging because language-specific edits interfere with one another, even when locate-then-edit methods
og AI要約 「VectraYX-Nano: A 42M-Parameter Spanish Cybersecurity Language Model with Curriculum Learning and Native Tool Use」 (arxiv-cs-cl) 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:2605.13989v1 Announce Type: new Abstract: We present VectraYX-Nano, a 41.95M-parameter decoder-only language model trained from scratch in Spanish for cybersecurity, with a Latin-American focus
og AI要約 「Mistletoe: Stealthy Acceleration-Collapse Attacks on Speculative Decoding」 (arxiv-cs-cl) 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:2605.14005v1 Announce Type: new Abstract: Speculative decoding has become a widely adopted technique for accelerating large language model (LLM) inference by drafting multiple candidate tokens a
og AI要約 「Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning」 (arxiv-cs-cl) 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:2605.14040v1 Announce Type: new Abstract: We audit the multimodal-physics evaluation pipeline end-to-end and document three undetected construction practices that distort how the field measures
og AI要約 「Derivation Prompting: A Logic-Based Method for Improving Retrieval-Augmented Generation」 (arxiv-cs-cl) 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:2605.14053v1 Announce Type: new Abstract: The application of Large Language Models to Question Answering has shown great promise, but important challenges such as hallucinations and erroneous re
AI要約 「PEML: Parameter-efficient Multi-Task Learning with Optimized Continuous Prompts」 (arxiv-cs-cl) 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:2605.14055v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for various tasks. Recently, there has been an increasin
AI要約 「Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents」 (arxiv-cs-cl) 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:2605.14057v1 Announce Type: new Abstract: Most existing dialogue systems are user-driven, primarily designed to fulfill user requests. However, in many critical real-world scenarios, a conversat
AI要約 「Distribution Corrected Offline Data Distillation for Large Language Models」 (arxiv-cs-cl) 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:2605.14071v1 Announce Type: new Abstract: Distilling reasoning traces from strong large language models into smaller ones is a promising route to improve intelligence in resource-constrained set
AI要約 「Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study」 (arxiv-cs-cl) 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:2605.14087v1 Announce Type: new Abstract: Large Language Models (LLMs), when trained on web-scale corpora, inherently absorb toxic patterns from their training data. This leads to ``toxic degene
AI要約 「When Evidence Conflicts: Uncertainty and Order Effects in Retrieval-Augmented Biomedical Question Answering」 (arxiv-cs-cl) 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…
EN arXiv:2605.14115v1 Announce Type: new Abstract: Biomedical retrieval-augmented large language models (LLMs) often face evidence that is incomplete, misleading, or internally contradictory, yet evaluat
AI要約 「Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards」 (arxiv-cs-cl) 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:2605.14117v1 Announce Type: new Abstract: An AI system for professional floor plan design must precisely control room dimensions and areas while respecting the desired connectivity between rooms
AI要約 「Polar probe linearly decodes semantic structures from LLMs」 (arxiv-cs-cl) 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:2605.14125v1 Announce Type: new Abstract: How do artificial neural networks bind concepts to form complex semantic structures? Here, we propose a simple neural code, whereby the existence and th
AI要約 「ROK-FORTRESS: Measuring the Effect of Geopolitical Transcreation for National Security and Public Safety」 (arxiv-cs-cl) 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:2605.14152v1 Announce Type: new Abstract: Safety evaluations for large language models (LLMs) increasingly target high-stakes National Security and Public Safety (NSPS) risks, yet multilingual s
AI要約 「BOOKMARKS: Efficient Active Storyline Memory for Role-playing」 (arxiv-cs-cl) 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:2605.14169v1 Announce Type: new Abstract: Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling)
AI要約 「Why Retrieval-Augmented Generation Fails: A Graph Perspective」 (arxiv-cs-cl) 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:2605.14192v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a powerful and widely used approach for improving large language models by grounding generation in retri
AI要約 「GradShield: Alignment Preserving Finetuning」 (arxiv-cs-cl) 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:2605.14194v1 Announce Type: new Abstract: Large Language Models (LLMs) pose a significant risk of safety misalignment after finetuning, as models can be compromised by both explicitly and implic
AI要約 「What Makes Words Hard? Sakura at BEA 2026 Shared Task on Vocabulary Difficulty Prediction」 (arxiv-cs-cl) 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:2605.14257v1 Announce Type: new Abstract: We describe two types of models for vocabulary difficulty prediction: a high-accuracy black-box model, which achieved the top shared task result in the
AI要約 「Auditing Agent Harness Safety」 (arxiv-cs-cl) 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:2605.14271v1 Announce Type: new Abstract: LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. Howev
AI要約 「Factorization-Error-Free Discrete Diffusion Language Model via Speculative Decoding」 (arxiv-cs-cl) 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:2605.14305v1 Announce Type: new Abstract: Discrete diffusion language models improve generation efficiency through parallel token prediction, but standard $X_0$ prediction methods introduce fact
AI要約 「Ideology Prediction of German Political Texts」 (arxiv-cs-cl) 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:2605.14352v1 Announce Type: new Abstract: Elections represent a crucial milestone in a nation's ongoing development. To better understand the political rhetoric from various movements, ranging f
AI要約 「LLM-based Detection of Manipulative Political Narratives」 (arxiv-cs-cl) 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:2605.14354v1 Announce Type: new Abstract: We present a new computational framework for detecting and structuring manipulative political narratives. A task that became more important due to the s
AI要約 「Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax」 (arxiv-cs-cl) 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…
EN arXiv:2605.14366v1 Announce Type: new Abstract: Extending large language models (LLMs) to low-resource languages often incurs an "alignment tax": improvements in the target language come at the cost o
AI要約 「Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement」 (arxiv-cs-cl) 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:2605.14368v1 Announce Type: new Abstract: Continuous diffusion language models lag behind autoregressive transformers, partly because diffusion is applied in spaces poorly suited to language den
AI要約 「Mitigating Data Scarcity in Psychological Defense Classification with Context-Aware Synthetic Augmentation」 (arxiv-cs-cl) 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…
EN arXiv:2605.14380v1 Announce Type: new Abstract: Psychological defense mechanisms (PDMs) are unconscious cognitive processes that modulate how individuals perceive and respond to emotional distress. Au
AI要約 「Agentic Recommender System with Hierarchical Belief-State Memory」 (arxiv-cs-cl) 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:2605.14401v1 Announce Type: new Abstract: Memory-augmented LLM agents have advanced personalized recommendation, yet existing approaches universally adopt flat memory representations that confla
AI要約 「Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation」 (arxiv-cs-cl) 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:2605.14404v1 Announce Type: new Abstract: While LLMs are increasingly used in commercial services, they pose privacy risks such as leakage of sensitive personally identifiable information (PII).
AI要約 「A Calculus-Based Framework for Determining Vocabulary Size in End-to-End ASR」 (arxiv-cs-cl) 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:2605.14427v1 Announce Type: new Abstract: In hybrid automatic speech recognition (ASR) systems, the vocabulary size is unambiguous, typically determined by the number of phones, bi-phones, or tr