Search: “claude”

DAYJOB: A Benchmark for Long-Horizon Professional Work

arXiv:2610.01306v1 Announce Type: new Abstract: Professional work often starts with a brief request that leaves the professional to work out what is needed, which documents matter, and whether the req

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Do Your Own Research: Learning to Forecast by Learning to Search

DGX agent

arXiv:2610.01955v1 Announce Type: new Abstract: Outcome-based reinforcement learning can train language models to forecast real-world events, but prior forecasting work either freezes research context

model-releasesarxiv-cs-lg

2 Oct 2026

How Much Can Language Models Gain from Test-Time Computation?

arXiv:2610.01110v1 Announce Type: new Abstract: How much can test-time computation improve a language model, and at what cost? Test-time scaling is widely proposed as a substitute for larger models, b

Legal Research Bench: Measuring End-to-End Reliability in Long-Horizon Legal Research Agents

arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute

OR for AI That Does OR: Routing LLMs up the Escalator inside the OSCAR Framework

arXiv:2610.00912v1 Announce Type: new Abstract: Large language models can translate business descriptions into optimization models, but executable code may misrepresent constraints or objectives. A so

ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research

arXiv:2610.02202v1 Announce Type: new Abstract: What makes great scientists great? Even as AI systems start to make progress on open problems, scientists remain far ahead of them at sensing which prio

The same model, with the same weights, scores 62% in one agent harness and 33% in another. @adithya_s_k and the @huggingface team just relea…

model-releasesclem-delangue--x

The same model, with the same weights, scores 62% in one agent harness and 33% in another. @adithya_s_k and the @huggingface team just released the ultimate guide to multi-harness RL, and it's one of

VeriHarness: Scaling Agentic Verification for Long-Horizon Tasks

arXiv:2610.00972v1 Announce Type: new Abstract: As LLM agents undertake increasingly complex, long-horizon tasks, verifying their outputs becomes increasingly challenging. We study how verification ca

VERITYGATE: A Four-Gate Schema-Level Faithfulness Framework and Paired Benchmark for Grounded LLM Narrations over Structured Evidence

arXiv:2610.00833v1 Announce Type: cross Abstract: Fluent LLM explanations may not follow the evidence from a structured system. We present VERITYGATE, a four-gate checker for declared evidence IDs, en

Video-Index: A Curated Meta-Benchmark for Video Understanding

model-releasesarxiv-cs-cv

arXiv:2610.00960v1 Announce Type: new Abstract: A video benchmark should reward the capability it claims to measure, yet models can exploit answer options, question text, or partial visual evidence. W

VISTA: A Visual Harness for Reasoning in an Interactive World

arXiv:2610.02200v1 Announce Type: new Abstract: We show that multimodal models possess strong reasoning abilities and that an appropriate harness can unlock their potential to solve tasks across diver

Yes! I think there is too much 'we're so early' self-congratulation here. Many senior leaders in companies are smart, motivated, and underst…

model-releasesethan-mollick--x

Yes! I think there is too much 'we're so early' self-congratulation here. Many senior leaders in companies are smart, motivated, and understand a lot about their business. Many are also technically ad

Anthropic urges Australia to consider 'conditional approval' for Big Tech to train models on copyrighted works, giving copyright holders a choice to opt out (Josh Butler/The Guardian)

Josh Butler / The Guardian: Anthropic urges Australia to consider “conditional approval” for Big Tech to train models on copyrighted works, giving copyright holders a choice to opt out — Maker of Clau

ArchitectureIQ: On the Measure of Training Intuition

arXiv:2609.39714v1 Announce Type: new Abstract: Top researchers have good intuition, but do language models have as good intuition about model training as top AI researchers? To measure model intuitio

b11320

model-releasesllama-cpp-releases

common : add LLM-jp-4.1 Harmony dialect handler (#29681) LLM-jp-4.1 uses the GPT-OSS format, but its tokenizer decodes a space after every special token and parallel tool calls are separated by <|end|

babe, wake up. Hugging Face just dropped a new banger article about RL training coding agents on different harnesses.

model-releasesclem-delangue--x

babe, wake up. Hugging Face just dropped a new banger article about RL training coding agents on different harnesses. 1/ Excited to release The ultimate guide to multi-harness RL The same model behave

Built a free, open-source Mac native swift AI agent Harness with actually usable computer use because we shouldn't need outrageous paid plans.

https://preview.redd.it/5w22g46ihssh1.png?width=2880&format=png&auto=webp&s=cbae24190847b3d80b919ce72d6703c9d1a5a52d The best agent experiences I tried (Dots/ GrokBot) all had an agent that can actual

model-releasesr-ollama

CompoWorld: Compositional Environment Scaling for General Agents

arXiv:2609.33665v2 Announce Type: replace Abstract: Automatically generated environments provide a scalable source of interaction data for training general agents. However, existing approaches mainly

From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.39566v1 Announce Type: new Abstract: Foundation models can serve as clinical agents through tool-use harnesses. However, conventional medical benchmarks assess reasoning over preselected ev

GraphForge: Training Working Agents with Graph-Anchored Workspace Synthesis

model-releasesarxiv-cs-cl

arXiv:2609.38923v1 Announce Type: new Abstract: Working agents need to read diverse files, coordinate tools, and produce deliverables. Training such agents requires tasks built on many real files with

KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy

arXiv:2609.38480v1 Announce Type: cross Abstract: Most clinical benchmarks evaluate language models (LMs) on diagnosis using complete case descriptions. In clinical practice, however, patients present

OpenCollab: A Multi-Agent Coding Framework with Programmable Collaboration and Controllable Runtime

arXiv:2609.38345v1 Announce Type: cross Abstract: Multi-agent coding systems are designed to tackle complex software engineering tasks through collaboration. However, existing evaluations typically as

Pretext: Defeating Malicious Skill Detection Frameworks for AI Agents

arXiv:2609.39607v1 Announce Type: cross Abstract: Skills extend an agent's capabilities by injecting instructions and information into the context, and are widely used by agents such as OpenClaw and C

RAIM: Robust Aggregation of Inexpensive Models for Hallucination Detection

arXiv:2609.39229v1 Announce Type: cross Abstract: Automatic evaluation of faithfulness increasingly relies on a large language model acting as a judge, yet the most reliable judges are proprietary fro

RankEvolve: A Reliable Multi-Agent Auto-Research Harness for Evolving Ranking Models

arXiv:2609.39551v1 Announce Type: new Abstract: Auto-research agents, LLM systems that propose, implement, train, and evaluate model changes across iterations, promise to automate applied ML's experim

Self-Spec Verifiable Code Generation

arXiv:2609.39568v1 Announce Type: cross Abstract: Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable g

The Backdrop Exposes What the World Around an Agent Costs It

arXiv:2609.38469v1 Announce Type: cross Abstract: Agent benchmarks test agents in worlds that stay still. Deployed agents work in worlds that other people also change. Someone texts the agent to send

The Invisible Language Tax: Token Premiums of French and Regional Languages in 2026 LLM Tokenizers, and a French-Optimized Prototype

arXiv:2609.39001v1 Announce Type: cross Abstract: LLM services are billed per token and context windows are measured in tokens, yet the number of tokens needed for the same content varies across langu

Accessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding Access

arXiv:2609.36129v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expa

AdviSD: Learning to Advise Frontier LLMs via Targeted Multi-Turn Self-Distillation

arXiv:2609.38142v1 Announce Type: new Abstract: A small trainable advisor can steer a frozen language-model executor using natural-language advice. In addition to learning from task rewards, the advis

Artificial Analysis says Gemini 4 Argon (high) matches GPT-6 Astra (max) on its Intelligence Index and has a 15% hallucination rate, compared with 51% for Astra (Artificial Analysis)

Artificial Analysis: Artificial Analysis says Gemini 4 Argon (high) matches GPT-6 Astra (max) on its Intelligence Index and has a 15% hallucination rate, compared with 51% for Astra — Google's new Gem

Auditable Long-Term Memory: A Deterministic Retrieval Chain Measured at 479/475 of 500 on LongMemEval-S

arXiv:2609.38021v1 Announce Type: cross Abstract: We evaluate an auditable long-term memory system on LongMemEval-S. Its retrieval chain uses hybrid candidate retrieval, cross-encoder reranking, cover

b11293

model-releasesllama-cpp-releases

ggml : add BF16 unary, GLU, binary and scale ops (CPU, CUDA) (#29675) ggml : add BF16 unary, GLU, binary and scale ops (CPU, CUDA) ggml-cpu : use per-op _bf16 functions for BF16 unary and GLU ops Assi

Code4Scene: Benchmarking Coding Agents for Constructing and Editing 3D Scenes

arXiv:2609.36777v1 Announce Type: new Abstract: Frontier coding agents can now write and execute code that authors 3D environments, but whether they reliably understand 3D structure and precisely cont

Evaluating the Effects of Prompt Perturbation on Bias and Hallucination in Large Language Models

arXiv:2609.35804v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities in various natural language processing tasks, leading to their widespread deployment a

Five local models, 6.8 GB of weights: my open-source Mac meeting notetaker

model-releasesr-localllama

https://preview.redd.it/xs01ds930nsh1.png?width=4800&format=png&auto=webp&s=939762bcf3fbd93e137d4f97e927dda38aaf30fd Back in July I shared LokalBot here. It's a free, open-source Mac app that records

Google rolls out Gemini 4 Argon to a small group of cybersecurity partners and says it outperforms GPT-6 Astra on certain coding and knowledge work benchmarks (Madison Mills/Axios)

Madison Mills / Axios: Google rolls out Gemini 4 Argon to a small group of cybersecurity partners and says it outperforms GPT-6 Astra on certain coding and knowledge work benchmarks — Google is unveil

Governing the Edge: Automating Commercial Property and Casualty Insurance Underwriting via a Hybrid Local-Cloud Multi-Agent Framework

arXiv:2609.37454v1 Announce Type: new Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a s

I built a free, local Qwen-Image 2.1 app for Apple Silicon Macs: multi-image edits, transparent PNGs and a node canvas

model-releasesr-stablediffusion

I built Image Studio, a local web app for Qwen-Image 2.1 on Apple Silicon. I had the model running on my Mac, but the only way to use it was the ComfyUI graph, and chaining edits meant wiring loaders,

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

Koa-action: Fast and Consistent Structured Decision Making with Generative LLMs

arXiv:2609.36115v1 Announce Type: new Abstract: Industry applications often demand low-latency classification, yet current large language model (LLM) approaches remain poorly suited for latency-critic

Large Language Models Exhibit Human-Like Bayesian Hypocrisy

model-releasesarxiv-cs-cl

arXiv:2609.35779v1 Announce Type: cross Abstract: Given recent achievements of large language models (LLMs), frontier models are expected to perform well on Bayesian reasoning tasks, at least as well

MCPTox: A Benchmark for Tool Poisoning Attack on Real-World MCP Servers

arXiv:2508.14925v2 Announce Type: replace-cross Abstract: By providing a standardized interface for LLM agents to interact with external tools, the Model Context Protocol (MCP) is quickly becoming a c

Sources: some Google employees say Gemini 4 performs well on benchmarks but struggles with some real-world coding tasks; Google disputes that characterization (Bloomberg)

Bloomberg: Sources: some Google employees say Gemini 4 performs well on benchmarks but struggles with some real-world coding tasks; Google disputes that characterization — As Alphabet Inc.'s Google pr

Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning

arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control c

Who Warmed the Archives? LLMs Overestimate Historical Warmth

model-releasesarxiv-cs-cl

arXiv:2609.37499v1 Announce Type: new Abstract: Historical archives are an under-used source for extending the instrumental climate record backward in time, and LLMs offer a way to extract the indices

50B+ MoEs with few active parameters, what's the sweet spot for intelligence, agent speed, and affordable fine-tuning?

model-releasesr-localllama

I’m building a Polish General purpose legal Model that drafts documents, answers questions using legal sources, and has enough coding ability to handle some automation. The workflow is very tool-heavy

29 Sept 2026

ActionEngine: From Reactive to Programmatic Web Agents via State Machine Memory

arXiv:2602.20502v2 Announce Type: replace-cross Abstract: Many web agents operate through a reactive execution loop: they observe the current interface, reason about the next action, execute it, and r