Search: “claude”

Ratchet: A Minimal Hygiene Recipe for Self-Evolving LLM Agents

arXiv:2605.22148v1 Announce Type: cross Abstract: Self-evolving skill libraries, pioneered by Voyager, let frozen LLM agents accumulate reusable knowledge without weight updates, yet recent evaluation

22 May 2026

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We desperately need better ways of evaluating models. Something that shows how helpful they are at working hand-in-hand with humans to help …

DGX agent

We desperately need better ways of evaluating models. Something that shows how helpful they are at working hand-in-hand with humans to help them get stuff done in a cooperative/iterative way. The Clau

model-releasesjeremy-howard--x

22 May 2026

Deltaynamics: Language-Based Representation for Inferring Rigid-Body Dynamics From Videos

model-releasesarxiv-cs-cv

arXiv:2605.20576v1 Announce Type: new Abstract: Inferring rigid-body physical states and properties from monocular videos is a fundamental step toward physics-based perception and simulation. Existing

Evolutionary Generation of Multi-Agent Systems

model-releasesarxiv-cs-lg

arXiv:2602.06511v3 Announce Type: replace Abstract: Large language model (LLM)-based multi-agent systems (MAS) show strong promise for complex reasoning, planning, and tool-augmented tasks, but design

Findings of the Counter Turing Test: AI-Generated Text Detection

arXiv:2605.20761v1 Announce Type: new Abstract: The rapid proliferation of AI-generated text has introduced significant challenges in maintaining the integrity of digital content. Advanced generative

Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search

arXiv:2605.20244v1 Announce Type: cross Abstract: We present Lean Refactor, a plug-and-play retrieval-augmented agentic framework for multi-objective, controllable, and version-robust refactoring of L

Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution

arXiv:2605.21465v1 Announce Type: new Abstract: In model-driven engineering, metamodel evolution leads to the need to adapt corresponding grammars to maintain consistency, which typically requires ted

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Cod…

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Coding agent, end to end. Frontend prototypes, multi-file refactor

model-releasesqwen--x

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists

arXiv:2605.20668v1 Announce Type: new Abstract: With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remai

Disentangling generalization and memorization in large language models using chess

arXiv:2601.16823v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit remarkable capabilities, yet it remains unclear to what extent these reflect sophisticated recall or genu

Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning

arXiv:2605.18871v1 Announce Type: cross Abstract: When Large Language Models produce structured outputs such as travel plans, code solutions, or multi-step proofs, individual reasoning steps may appea

DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs

arXiv:2605.18915v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are vulnerable to jailbreak attacks, which can elicit harmful responses from MLLMs. Many MLLMs support multi-

Does Code Cleanliness Affect Coding Agents? A Controlled Minimal-Pair Study

arXiv:2605.20049v1 Announce Type: cross Abstract: As autonomous coding agents see rapid adoption, their evaluation has primarily focused on task completion rates holding the target codebase fixed. Thi

Less Back-and-Forth: A Comparative Study of Structured Prompting

arXiv:2605.20149v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used for open-ended tasks, but underspecified prompts can lead to low-quality answers and additional interacti

ReacTOD: Bounded Neuro-Symbolic Agentic NLU for Zero-Shot Dialogue State Tracking

arXiv:2605.19077v1 Announce Type: cross Abstract: Task-oriented dialogue systems -- handling transactions, reservations, and service requests -- require predictable behavior, yet the moderately-sized

Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post o…

Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post on how I am using @FireworksAI_HQ Agent to automate LLM fine-

model-releasesdair-ai--x

1GC-7RC: One Graphic Card -- Seven Research Challenges! How Good Are AI Agents at Doing Your Job?

arXiv:2605.17046v1 Announce Type: cross Abstract: Autonomous AI coding agents are becoming a core tool for ML practitioners in industry and research alike. Despite this growing adoption, no standardiz

AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents

arXiv:2605.16819v1 Announce Type: cross Abstract: GPU kernel optimization is increasingly critical for efficient deep learning systems, but writing high-performance kernels still requires substantial

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling

arXiv:2605.17971v1 Announce Type: cross Abstract: Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuri

Benchmarking Mythos-Linked Bug Rediscovery

arXiv:2605.17416v1 Announce Type: cross Abstract: Anthropic's April 2026 Mythos materials combine benchmark claims with concrete bug-finding stories across OpenBSD, FreeBSD, Linux, FFmpeg, and browser

Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench

arXiv:2605.17079v1 Announce Type: cross Abstract: LLMs are increasingly used as ``digital consumers'' to simulate public opinion, pre-test marketing decisions, and anticipate audience response. Howeve

Causely: A Causal Intelligence Layer for Enterprise AI A Benchmark Study on SRE and Reliability Workflows

arXiv:2605.18327v1 Announce Type: new Abstract: AI agents deployed into SRE workflows currently derive their understanding of environment state from raw observability telemetry at query time, paying a

ContractBench: Can LLM Agents Preserve Observation Contracts?

arXiv:2605.17281v1 Announce Type: cross Abstract: Tool-augmented LLM agents call APIs whose intermediate outputs, such as presigned URLs, session tokens, and OAuth state parameters, are observation co

Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?

model-releasesarxiv-cs-lg

arXiv:2602.18895v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promise in translating model-based explanations into human-readable narratives. This study evaluates w

CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability

arXiv:2602.03012v2 Announce Type: replace-cross Abstract: Evaluating and improving the security capabilities of code agents requires high-quality, executable vulnerability tasks. However, existing wor

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs

arXiv:2511.12710v2 Announce Type: replace Abstract: Automated red teaming frameworks for Large Language Models (LLMs) have become increasingly sophisticated, yet many still formulate attack optimizati

Fidelity Probes for Specification--Code Alignment

arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c

Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIs

arXiv:2605.17558v1 Announce Type: cross Abstract: Training tool-calling agents requires large-scale trajectory data with verifiable labels, yet existing approaches either synthesize environments that

Generative Artificial Intelligence for Literature Reviews

arXiv:2605.16475v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI), based on large-language models (LLMs), such as ChatGPT, has taken organizations, academia, and the public

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL

model-releasesarxiv-cs-lg

arXiv:2605.17792v1 Announce Type: new Abstract: Calibrating distributed hydrologic models is a critical bottleneck across operational water resources management - streamflow prediction, reservoir oper

Learning How to Cube

arXiv:2605.16632v1 Announce Type: cross Abstract: Despite the effectiveness of Cube-and-Conquer (C&C) for solving challenging Boolean Satisfiability (SAT) problems, no prior work has shown that transf

LivePI: More Realistic Benchmarking of Agents Against Indirect Prompt Injectio

arXiv:2605.17986v1 Announce Type: cross Abstract: AI agents such as OpenClaw are increasingly deployed in local workflows with access to external tools. This creates indirect prompt-injection (IPI) ri

MANTA: Multi-turn Assessment for Nonhuman Thinking & Alignment

arXiv:2605.16301v1 Announce Type: cross Abstract: Single-turn benchmarks such as AnimalHarmBench (AHB) have established important baselines for measuring animal welfare alignment in large language mod

Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting

arXiv:2510.10528v3 Announce Type: replace Abstract: Large reasoning models (LRMs) have demonstrated remarkable proficiency in tackling complex tasks through step-by-step thinking. However, this length

'One thing that we've been seeing recently is that inference benchmarks don't really match production workloads that well.' - @realDanFu, VP…

model-releasestogether-ai--x

'One thing that we've been seeing recently is that inference benchmarks don't really match production workloads that well.' - @realDanFu, VP of Kernels When you're running dozens of concurrent coding

OpenJarvis: Personal AI, On Personal Devices

arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local

Prompts Don't Protect: Architectural Enforcement via MCP Proxy for LLM Tool Access Control

arXiv:2605.18414v1 Announce Type: cross Abstract: Large language models increasingly operate as autonomous agents that select and invoke tools from large registries. We identify a critical gap: when u

Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback

arXiv:2605.17448v1 Announce Type: cross Abstract: Computer-aided design (CAD) is the backbone of modern industrial design, yet learned CAD generators still fall short of real engineering pipelines: th

ShareChat: A Dataset of Chatbot Conversations in the Wild

arXiv:2512.17843v4 Announce Type: replace-cross Abstract: By evaluating Large Language Models (LLMs) through uniform, text-only interfaces, current academic benchmarks obscure how the unique designs a

STT-Arena: A More Realistic Environment for Tool-Using with Spatio-Temporal Dynamics

arXiv:2605.18548v1 Announce Type: cross Abstract: Large language models (LLMs) deployed in real-world agentic applications must be capable of replanning and adapting when mid-task disruptions invalida

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate

WEBSERV: A Full-Stack and RL-Ready Web Environment for Training Web Agents at Scale

arXiv:2510.16252v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for web agents demands environments that are both effective for evaluation and efficient enough for large-scale on

When AI Tells You What You Want to Hear: Sycophantic Behavior of Large Language Models in Dementia Care Settings

arXiv:2605.16288v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in clinical and care settings. This exploratory study investigates whether LLMs exhibit sycophantic

WhiteTesseract: Reframing the Interpretation of Cultural Heritage through XR and Conversational AI

arXiv:2605.16972v1 Announce Type: cross Abstract: Cultural heritage exhibitions often struggle to sustain attention and support reflective engagement. Physical exhibitions rely on fixed interpretive a

A3D: Agentic AI flow for autonomous Accelerator Design

arXiv:2605.15237v1 Announce Type: cross Abstract: Accelerating applications through the design of hardware accelerators can significantly enhance system performance and energy efficiency. Despite adva

Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries

arXiv:2605.15680v1 Announce Type: new Abstract: Online patient inquiries are often informal, incomplete, and written before professional assessment, yet they must still be routed to an appropriate lev

RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades

arXiv:2605.15846v1 Announce Type: cross Abstract: Coding agents are increasingly deployed in real software development, where a single version iteration requires months of coordinated work across many

VideoGameBench: Can Vision-Language Models complete popular video games?

arXiv:2505.18134v3 Announce Type: replace Abstract: Vision-language models (VLMs) have achieved strong results on coding and math benchmarks that are challenging for humans, yet their ability to perfo