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Showing 91–120 of 439
  • arXiv cs.CL (Computation and Language) · EN Developer Tools
    SCRBench: Beyond Equivalence Checking for Semantic Change Reasoning in Code
    Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Developer Tools
    Digital sovereignty in professional translation workflows: a case study of migrating from Windows to Linux
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    Enhancing Knowledge Entity Relation Extraction in Abstracts and Full-text Content of Academic Articles Using Large Language Models
    Neural Network Natural Language Processing (NLP)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    DAPS: Dependency-Aware Premise Selection for LLM Theorem Proving
    Deep Learning Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Developer Tools
    Enhancing Sentiment Classification on Small Datasets through Data Augmentation and Transfer Learning
    Machine Learning Natural Language Processing (NLP) Transformer
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • Stratechery (free posts) · EN Developer Tools
    Sharp Tech on Video: Anthropic’s S-1 and What It Means for Meta and Muse, You Can See Everything, and Brewers!
    Stratechery's Sharp Tech launches on video, with episode on Anthropic's S-1
    Anthropic Meta
    Stratechery's Sharp Tech podcast is now available on video for the first time, with three ways to watch: YouTube, Spotify, and Stratechery itself. The episode's title lists Anthropic's S-1 and what it means for Meta and Muse, a segment called "You Can See Everything," and the Brewers. The excerpt is brief, so the details of each discussion are not covered here.
    Read original (Stratechery (free posts)) ↗
  • arXiv cs.CL (Computation and Language) · EN Multimodal
    KEEPER: Learning Control-Sufficient Textual Memory for Long-Horizon LLM Agents
    AI Agents Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • OpenAI Blog · EN Developer Tools
    Making it easier for websites to express AI training preferences
    OpenAI to honor shared robots.txt signal on AI training preferences
    OpenAI
    OpenAI says it will honor a shared robots.txt signal that lets website operators communicate their AI training preferences to participating providers. The signal is meant to give site owners a common way to state those preferences.
    Read original (OpenAI Blog) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    A prospective randomized study of patient-centered AI for clinical visit preparation
    Google
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    Hybrid Computer Use: A Unified Programmatic, Semantic, and Visual Interface for General Agents
    AI Agents Neural Network Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    ProSearch: Benchmarking Multi-Constraint Protocol Retrieval in Experimental Science
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Comparative Evaluation of LLM-Based Review Paradigms for Academic Paper Quality Assessment
    Neural Network
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  • ITmedia AI+ · JA New Model Releases
    Meta Ray-Banで向かいの席から撮影→指の動きからスマホのパスワードを解読する盗み見攻撃
    Smart-glasses video of finger movements can crack phone passwords
    Inference Meta
    Tel Aviv University researchers presented 'Watch and Crack,' a paper showing that passwords can be inferred from finger movements recorded by smart glasses. The shoulder-surfing attack films from across the table with Meta Ray-Ban glasses to read smartphone passwords.
    Read original (ITmedia AI+) ↗
  • ITmedia AI+ · JA New Model Releases
    国産LLM「Sarashina」に初の「思考モデル」 ツール呼び出しやWeb検索性能が向上 APIで提供
    SB Intuitions launches Sarashina's first reasoning model
    SoftBank-backed SB Intuitions has announced Sarashina3.2 mini thinking, the first reasoning model in its from-scratch Japanese Sarashina LLM series. It spends more time on output to improve accuracy, offers better tool calling and web search, and is available via API.
    Read original (ITmedia AI+) ↗
  • Simon Willison's Weblog · EN New Model Releases
    API credits benefit for eligible ChatGPT subscriptions
    OpenAI now gives $100–$500/month ChatGPT subscribers matching API credits
    Anthropic Claude GPT Neural Network OpenAI
    OpenAI has launched a benefit giving ChatGPT subscribers on $100, $200 or $500 monthly plans an equivalent amount of API credits to apply to an API organization. It mirrors the deal Anthropic announced earlier this month for Max and Team subscribers. The author subscribes to both and may build public demos now that credits are covered.
    Read original (Simon Willison's Weblog) ↗
  • IEEE Spectrum (AI section) · EN Developer Tools
    Consumer Appetite for Personal AI Goes Mainstream
    Consumer demand for personal AI goes mainstream as wearables rise
    Retrieval-Augmented Generation (RAG)
    A Qualcomm-sponsored piece says consumers want AI that helps with daily life rather than generic tools. It argues context-aware wearables are shifting from passive notification accessories to proactive companions, with the AI itself becoming the interface and the smartphone no longer the center.
    Read original (IEEE Spectrum (AI section)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    Elucidating the Design Space of LM Data Attribution
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Funding & M&A
    Luggage re-identification: A study of strategies towards a real-world application
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    world2vec: Mechanistic world models through latent dynamics learning
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Probing Spatial State Representations in Visual Foundation Models
    Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    ShallowDefend: Harnessing Shallow Safety Alignment for Multi-Turn Defender
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Testimony from Timelines: Evidence-Grounded Significance Testing of Temporal Clinical Hypotheses
    Software Engineering
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  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    An ODE-based Sampler for Discrete Diffusion Models
    Software Engineering
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  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Difficulty Calibration Across Time for Membership Inference in Diffusion Models
    Inference Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    When to Assist and What to Suggest: Joint Gating and Memory-Grounded Hint Generation in One Compact Decoder
    Llama
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Agents & Tool Use
    Collaborative AI agents for autonomous experimental research with solid-state quantum spins
    AI Agents
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    Multistatic ISAC with Deep Learning-Based Clutter Suppression for 5G and Beyond
    Deep Learning Machine Learning Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Multimodal
    VeriCUA: Verification as Agentic Exploration for Computer-Using Agents
    AI Agents Computer Vision Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    PIVOT: Progressive Intervention via Online Teacher Correction
    Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Inference & Efficiency
    Every Token Needs Its Own Teacher: Multi-teacher Adaptive On-policy Self-distillation
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗