Search: “gpt”

Planning with the Views via Scene Self-Exploration

arXiv:2605.29563v1 Announce Type: new Abstract: Can VLMs predict how each camera move changes the view, and plan many such moves ahead? We call this capability view planning, requiring (1)understandin

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PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers

DGX agent

arXiv:2605.30094v1 Announce Type: new Abstract: Poker is a landmark challenge for artificial intelligence. The dominant approach relies on equilibrium solvers built on counterfactual regret minimizati

model-releasesarxiv-cs-ai

29 May 2026

Reasoning Theater: Disentangling Model Beliefs from Chain-of-Thought

arXiv:2603.05488v4 Announce Type: replace-cross Abstract: We provide evidence of performative chain-of-thought (CoT) in reasoning models, where a model becomes strongly confident in its final answer,

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents

arXiv:2509.23694v5 Announce Type: replace Abstract: Search agents connect LLMs to the Internet, enabling them to access broader and more up-to-date information. However, this also introduces a new thr

SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers

arXiv:2605.29059v1 Announce Type: cross Abstract: Smart contract decompilation aims to recover high-level source code from bytecode, but evaluating decompilers remains difficult because existing studi

SMolLM: Small Language Models Learn Small Molecular Grammar

arXiv:2605.06322v2 Announce Type: replace Abstract: Language models for molecular design have scaled to hundreds of millions of parameters, yet how they learn chemical grammar is poorly understood. We

Text-Preserving Lossy Text Compression: A Study of Strategic Deletion and LLM Reconstruction

arXiv:2605.29000v1 Announce Type: new Abstract: Traditional lossless text compression preserves every byte, but its gains on natural language are often modest in realistic operating regimes. We study

The Price Reversal Phenomenon: When Cheaper Reasoning Models Cost More

arXiv:2603.23971v2 Announce Type: replace-cross Abstract: Developers and consumers increasingly choose reasoning models (RMs) based on their listed API prices. However, how accurately do these prices

Trends in AI and Human-AI Interaction in Clinical Trials -- A Hybrid Human-AI Exploration

arXiv:2605.29096v1 Announce Type: new Abstract: This paper examines records retrieved from the ClinicalTrials.gov registry to characterize temporal trends in AI terminology and the geographical distri

We’re taking steps to accelerate defensive progress in biology: - Launching Rosalind Biodefense to help trusted builders develop new biodefe…

We’re taking steps to accelerate defensive progress in biology: - Launching Rosalind Biodefense to help trusted builders develop new biodefense and pandemic preparedness capabilities. - Expanding trus

model-releasesopenai--x

Automating Formal Verification with Agent-Guided Tree Search

arXiv:2605.27485v1 Announce Type: cross Abstract: Formal verification offers a path to provably correct software, but writing verified code remains expensive enough that the technique is rarely used i

Agents

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation

arXiv:2605.28655v1 Announce Type: new Abstract: Scientific research proceeds through iterative cycles of hypothesis generation, experiment design, execution, and revision. AI agents can automate parts

agentsarxiv-cs-ai

CiteCheck: Retrieval-Grounded Detection of LLM Citation Hallucinations in Scientific Text

arXiv:2605.27700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate scientific reports, but they can produce references that appear plausible while contain

ClinConsensus: A Physician-Calibrated Benchmark for Evaluating Clinical Rubric Coverage in Chinese Medical LLMs

arXiv:2603.02097v5 Announce Type: replace Abstract: Open-ended medical LLM evaluation remains weakly grounded in physician-calibrated coverage of clinically relevant response criteria, especially in l

Coherence Collapse: Diagnosing Why Code Agents Fail After Reaching the Right Code

arXiv:2603.24631v2 Announce Type: replace-cross Abstract: Code agents resolve 65-70% of SWE-bench Verified issues, but Pass@1 cannot tell us why the rest fail, and, as we show, capable-model failures

Cultural Fidelity in English-to-Hindi Translation: A Preservation-Fluency Frontier for Gender Recoverability

arXiv:2605.27654v1 Announce Type: cross Abstract: Generative translation systems are cultural technologies because they decide how socially meaningful cues are rendered within culturally specific gram

Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models

arXiv:2512.00349v2 Announce Type: replace Abstract: Are frontier AI systems becoming more capable? Certainly. Yet such progress is not an unalloyed blessing but rather a Trojan horse: behind their per

DecomposeRL: Learning to Ask Useful, Informative, and Diverse Questions for Semi-Supervised, Traceable Claim Verification

arXiv:2605.27858v1 Announce Type: cross Abstract: Claim verification splits between end-to-end classifiers that are accurate but yields no inspectable traces, and decomposition-based methods produce i

Do Models Know Why They Changed Their Mind? Interpretability and Faithfulness of Chain-of-Thought Under Knowledge Conflict

arXiv:2605.27773v1 Announce Type: cross Abstract: When a language model sees a document contradicting its training knowledge, it must choose: follow the document or trust itself. Prior work proved thi

From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons

arXiv:2605.27387v1 Announce Type: cross Abstract: Diffusion models promise efficient parallel text generation but rely on bidirectional attention, creating a structural mismatch with pre-trained Autor

safetyarxiv-cs-ai

Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks

arXiv:2605.27595v1 Announce Type: cross Abstract: Large Language Models (LLMs) are being rapidly adopted in agricultural imaging applications, ranging from crop interpretation to synthetic field image

Hurwitz Quaternion Multiplicative Quantization for KV Cache Compression

arXiv:2605.27646v1 Announce Type: cross Abstract: We propose extbf{Hurwitz Quaternion Multiplicative Quantization (HQMQ)}, a extbf{calibration-free} method for KV cache compression of large language m

LCO: LLM-based Constraint Optimization for Safer Agentic LLMs in Real-world Tasks

arXiv:2605.27375v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly acting as autonomous agents, but their continuous interaction with the environment can lead to in-context

Applications

Measuring Massive Multitask Chinese Understanding

arXiv:2304.12986v3 Announce Type: replace-cross Abstract: The development of large-scale Chinese language models is flourishing, yet there is a lack of corresponding capability assessments. Therefore,

applicationsarxiv-cs-ai

MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents

arXiv:2605.27853v1 Announce Type: new Abstract: We present MolLingo, a multi-agent system that emulates the reasoning process of a chemist to automate molecular design. Existing LLM-based approaches e

PAST2HARM: A Simple Adaptive Past Tense Attack for Jailbreaking Multimodal AI

arXiv:2605.27545v1 Announce Type: new Abstract: Jailbreak attacks on multimodal AI systems remain underexplored, even though unsafe image generation can have more severe consequences than unsafe text

Periodic RoPE for Infinite Context LLMs

arXiv:2605.27980v1 Announce Type: cross Abstract: The ability to process ultra-long contexts is crucial for large language models (LLMs) to perform long-horizon tasks. While recent efforts have extend

Pruning and Distilling Mixture-of-Experts into Dense Language Models

arXiv:2605.28207v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory,

ReflexGrad: Within-Episode Failure Recovery in LLM Agents via Progress-Gated Dual-Process Routing

arXiv:2511.14584v3 Announce Type: replace-cross Abstract: We present ReflexGrad, a dual-process architecture for within-episode failure recovery in LLM agents without demonstrations. When agents commi

Agents

Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agents

arXiv:2605.27955v1 Announce Type: cross Abstract: Markdown skill libraries for LLM agents ship as free-form prose, forcing the agent to re-derive both the input schema and the concrete invocation synt

agentsarxiv-cs-cl

Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis

arXiv:2605.27401v1 Announce Type: cross Abstract: There is a growing interest in utilizing synthetic populations for a diverse range of applications. At the same time, we are witnessing a tremendous g

A Dataset of Robot-Patient and Doctor-Patient Medical Dialogues for Spoken Language Processing Tasks

arXiv:2605.26747v1 Announce Type: new Abstract: Large Language Models (LLMs) have brought huge improvements to Artificial Intelligence (AI), which can be applied to general-purpose tasks. However, the

AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations

arXiv:2605.26179v1 Announce Type: cross Abstract: Density functional theory (DFT) serves as the basis for computational discovery in materials science and chemistry, yet each calculation demands exten

BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing?

arXiv:2603.03194v2 Announce Type: replace Abstract: Current code-agent benchmarks primarily evaluate localized issue resolution within a single target repository, leaving under-tested many software en

Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training

arXiv:2605.26484v1 Announce Type: new Abstract: Model merging has emerged as a lightweight paradigm for enhancing Large Language Models (LLMs), yet its underlying mechanisms remain poorly understood.

GeoFaith: A Spatio-Temporal Dual View of Faithful Chain-of-Thought

arXiv:2605.26893v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has advanced large language models (LLMs), but outcome-based supervision leads to pervasive post-hoc rationalization,

HTMLCure: Turning Browser Experience into State Guided Repair for Interactive HTML

arXiv:2605.26807v1 Announce Type: cross Abstract: LLMs can now produce full HTML pages, but many of those pages are only superficially correct: they render once, then fail under scroll, hover, click,

KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models

arXiv:2605.26947v1 Announce Type: new Abstract: Kazakh is underrepresented in resources for evaluating the safety behavior of large language models. We present KZ-SafetyPrompts, a Kazakh prompt datase

safetyarxiv-cs-cl

LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations?

arXiv:2605.26781v1 Announce Type: new Abstract: Advanced Large Multimodal Models (LMMs) have demonstrated impressive performance in K-12 reasoning tasks, exhibiting great promise as intelligent tutors

LLMs versus the Halting Problem: Characterizing Program Termination Reasoning

arXiv:2601.18987v5 Announce Type: replace-cross Abstract: Determining whether a program terminates is a central problem in computer science. Turing's Halting Problem established termination as undecid

MechRL: Reinforcement Learning Agents Perform Circuit Discovery for Mechanistic Interpretability

arXiv:2605.26343v1 Announce Type: new Abstract: Mechanistic interpretability has identified small sets of attention heads that implement specific behaviours in transformer language models, but recover

safetyarxiv-cs-lg

PersianMedQA: Evaluating Large Language Models on a Persian-English Bilingual Medical Question Answering Benchmark

arXiv:2506.00250v4 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable performance on a wide range of Natural Language Processing (NLP) benchmarks, often surpassing

Shopping Companion: A Memory-Augmented LLM Agent for Real-World E-Commerce Tasks

arXiv:2603.14864v2 Announce Type: replace Abstract: In e-commerce, LLM agents show promise for shopping tasks such as recommendations, budget management, and bundle deals, where accurately capturing u

SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning

arXiv:2603.28730v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown impressive capabilities across diverse tasks, motivating efforts to leverage these models to supervis

Research

The Daily Dose: Workflow-Integrated Large Language Model Automation for Clinical Summarization and Trial Identification in Radiation Oncology

arXiv:2605.26346v1 Announce Type: new Abstract: Objective: To describe the design and early clinical evaluation of The Daily Dose (TDD), an LLM-driven, automated clinical summarization and clinical-tr

researcharxiv-cs-cl

The Stability of Singular Distribution: A Spectral Perspective on the Two-Phase Dynamics of Language Model Pre-training

arXiv:2605.26489v1 Announce Type: new Abstract: Large language model pre-training typically exhibits a two-phase trajectory: a fast initial loss drop followed by a prolonged slow improvement. We ident

Research

Touch-R1: Reinforcing Touch Reasoning in MLLMs

arXiv:2605.27154v1 Announce Type: new Abstract: While rule-based reinforcement learning has recently catalyzed explicit reasoning in multimodal models, tactile reasoning remains largely underexplored.

researcharxiv-cs-cv

VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models

arXiv:2510.17759v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) extend large language models with visual reasoning, but their multimodal design also introduces new, underexplor

safetyarxiv-cs-cl