Search: “reasoning”

A Quantitative Study of Sustained Focus in Large Language Models via Repetitive Deterministic Prediction Tasks

arXiv:2511.00763v3 Announce Type: replace Abstract: We investigate the performance of large language models (LLMs) on repetitive deterministic prediction tasks and study how the sequence accuracy rate

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Advancing Entropy-Level Credit Assignment in RLVR via Proximal Entropy Policy Optimization

DGX agent

arXiv:2609.39402v1 Announce Type: new Abstract: Value-model-free RLVR methods such as GRPO assign uniform advantages to all tokens in a rollout, ignoring that tokens contribute unequally. Recent metho

model-releasesarxiv-cs-ai

1 Oct 2026

After a Decade: Bringing Shadow Removal into the Real World with Agentic Training Data

arXiv:2609.38607v1 Announce Type: cross Abstract: Shadow removal looks nearly solved on established benchmarks, yet remains brittle in the real world. Models have advanced; the paired training data th

Agent Error Dataset: Scaling 50,000 Error--Diagnosis Pairs for Failure Analysis and Error-Aware Post-Training

arXiv:2609.40111v1 Announce Type: new Abstract: An unsuccessful LLM agent rollout contains more information than its final reward: the observations available to the agent, the actions it chose, and th

AI Agents are Vulnerable to Radicalization

arXiv:2609.38296v1 Announce Type: new Abstract: Large language models (LLMs) can influence people's beliefs, yet little is known about whether and how they can manipulate each other. To investigate th

AIMS: An Agentic AI Framework for Sim-to-Real Multi-Modal ISAC

arXiv:2609.39964v1 Announce Type: new Abstract: Multi-modal integrated sensing and communication (ISAC) enables environmental perception and reliable connectivity for intelligent wireless networks. Da

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

Argus: Academic Integrity in the Era of Generative AI

arXiv:2609.36073v1 Announce Type: cross Abstract: The rapid proliferation of large language models (LLMs) in the context of education has introduced significant challenges in enforcement of academic i

ASENA: Self-evolving Agents for Embodied Navigation

arXiv:2609.39207v1 Announce Type: new Abstract: We present ASENA, an embodied agent system that connects general-purpose coding agents to robot sensing, computation, supervised execution, and persiste

safetyarxiv-cs-ro

AutoDataBench: A Data-centric Testbed for Accelerating Auto Research

arXiv:2609.40097v1 Announce Type: new Abstract: Existing auto-research benchmarks often entangle multiple sources of improvement, including training frameworks, hyperparameters, compute budgets, and d

agentsarxiv-cs-cl

Blackboard Intelligence Can Surpass Autoregressive on Globally Constrained Problems

arXiv:2609.38806v1 Announce Type: cross Abstract: Next-token prediction has driven remarkable progress in large language models, yet a growing body of evidence suggests that they can struggle on probl

tutorialsarxiv-cs-cl

Can Computation from Earlier Problems Help LLMs Solve New Ones?

arXiv:2609.39394v1 Announce Type: new Abstract: Large language models often solve independent problems in the same conversation. Can computation from earlier problems help them solve new ones? To answ

ChronoGraph: Functional 4D Scene Graphs with Vision-Language Models for Interaction Understanding and Grounded Planning

arXiv:2609.39665v1 Announce Type: new Abstract: Embodied agents must determine where to act, anticipate the resulting scene changes, and interpret observed outcomes to guide subsequent actions. This r

tutorialsarxiv-cs-ai

Co-Evolving Agents: Learning from Failures as Hard Negatives

arXiv:2511.22254v5 Announce Type: replace Abstract: Self-evolving agents improve their performance on long-horizon tasks by learning from their own interactions with an environment. A common approach

Coding Agents for Coding Theory

arXiv:2609.39081v1 Announce Type: cross Abstract: We spent five weeks using an LLM coding agent on open problems in coding theory: finding large sets of four-letter words, such as DNA barcodes, that s

CoEvoWhen: Policy-Tool Coevolution for Ultra-Long Video Temporal Grounding

arXiv:2609.40048v1 Announce Type: new Abstract: Ultra-long video temporal grounding requires balancing long-range evidence search with fine-grained event understanding under a limited visual budget, y

safetyarxiv-cs-cv

ComputerSD: Online Self-Distillation from Real-Time Feedback for Computer-Use Agents

arXiv:2609.40253v1 Announce Type: cross Abstract: Online training enables computer-use agents (CUAs) to improve through interaction with executable environments. However, existing methods primarily re

Conformal Factuality Control for Multi-Hop Retrieval-Augmented Generation

arXiv:2609.38222v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can ground large language models in external evidence, but retrieved context does not guarantee that generated clai

Coverage Before Control: Route-Instruction Grounding and Steering for Controllable Retrosynthesis

arXiv:2609.39955v1 Announce Type: new Abstract: Single-step retrosynthesis models are commonly evaluated by their ability to recover recorded reactions. In practice, chemists may need to choose among

tutorialsarxiv-cs-ai

CoVisco: Codec-Native Vision Encoder with Native Token Compression for Unified Image-Video Understanding

arXiv:2609.39924v1 Announce Type: cross Abstract: Vision-language models face a fundamental scaling bottleneck: the number of visual tokens grows with both temporal duration and spatial resolution, ma

tutorialsarxiv-cs-ai

Distill the Visual Evidence, Not Just the Answer: Cross-World On-Policy Distillation for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.38777v1 Announce Type: new Abstract: A central goal of vision-language model (VLM) distillation is to transfer both the teacher's language capabilities and its visual understanding. However

Drift Inspector: Exploring and Measuring Scientific Drift with Atomic Contribution Claims

arXiv:2609.39710v1 Announce Type: new Abstract: Scientific abstracts mix contributions with background, motivation, and meta-language, so tools that read them as-is cannot separate what a field produc

DrivingBench: Can Vision-Language Models Drive a Toyota Corolla?

arXiv:2609.38948v1 Announce Type: cross Abstract: Frontier models excel at many digital benchmarks, yet their ability to drive a real car, an everyday human skill, remains largely untested. We present

EHR2Trace: Auditable EHR Data Infrastructure for Patient World Models and Clinical Agents

arXiv:2609.38193v1 Announce Type: cross Abstract: Patient world models and clinical agents aim to predict changes in patients' health and support clinical work. Developing these systems requires relia

Eigenism: Ethics for a Human-AI Future

arXiv:2606.12420v2 Announce Type: replace-cross Abstract: Our concepts of survival and self-interest were built for single, continuous biological lives. These ideas break down when applied to artifici

Evaluating Whether GPT-6 Astra Performs Unsanctioned Supply-Chain Attacks

arXiv:2609.38415v1 Announce Type: cross Abstract: This technical report presents an alignment evaluation developed and performed by the UK AI Security Institute for assessing whether advanced AI syste

EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery

arXiv:2609.40340v1 Announce Type: new Abstract: Evolutionary search with large language models (LLMs) can stall when progress requires external knowledge the model lacks. Supplying relevant documents

EvoSteer: Online Self-Evolving Graph Orchestration via Reference-Anchored Credit Assignment

arXiv:2609.38661v1 Announce Type: new Abstract: In recent years, LLM-based multi-agent systems have been widely applied to orchestrate tool-using agents into executable communication graphs. However,

False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents

arXiv:2609.39102v1 Announce Type: cross Abstract: Self-evolving search agents build their own training curricula by jointly optimizing a proposer that generates questions and a solver that answers the

Fine-Tuning Diffusion Language Models with Context Selection and Target Weighting

arXiv:2609.38385v1 Announce Type: new Abstract: Supervised fine-tuning of discrete diffusion language models masks some response tokens and trains the model to recover their original values from the v

Applications

From Codebase to Culprit (C2C): Reducing the Search Space for Bugs with Semantic Retrieval and Hierarchical Reinforcement Learning

arXiv:2609.38402v1 Announce Type: cross Abstract: We introduce C2C (From Codebase to Culprit), a framework for precise bug localization that progressively reduces the debugging search space across mul

applicationsarxiv-cs-lg

From Solo to Social Learning: Characterizing Recursive Social Improvement in LLMs

arXiv:2609.38516v1 Announce Type: cross Abstract: Large language models (LLMs) can now improve themselves by revising the instructions they follow, and LLM agents are increasingly orchestrated to work

Fyan: A Human--AI Harness with Semantic Auditing for Document-Level Formalization

arXiv:2609.39228v1 Announce Type: new Abstract: We present FYAN, a human--AI harness for document-level mathematical formalization. Rather than treating theorems in isolation, FYAN coordinates an end-

H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model

arXiv:2602.11291v3 Announce Type: replace Abstract: World models are becoming central to robotic planning and control by predicting future state transitions. Existing approaches mainly rely on visual,

researcharxiv-cs-ro

Hard-Gate Candidacy in a Deployed Validator Suite

arXiv:2609.39037v1 Announce Type: cross Abstract: Before a validator can be promoted to a hard gate on a deployment pipeline, it has to be shown that its firing separates outputs that reach users in w

Hard-Region Supervision: #1 on the Waymo Open Dataset 2D Video Panoptic Segmentation Leaderboard

arXiv:2609.38714v1 Announce Type: new Abstract: We describe our winning entry to the Waymo Open Dataset 2D Video Panoptic Segmentation Challenge. The task asks for a semantic class at every pixel of e

researcharxiv-cs-cv

IronMind: Scaling Humanoid Dexterous Manipulation via Camera-Space Ego-Centric Pretraining

arXiv:2609.39403v1 Announce Type: new Abstract: Egocentric human video offers a scalable data source for dexterous manipulation, yet using it to train humanoid robots presents two challenges: (1) an e

researcharxiv-cs-ro

Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs

arXiv:2609.38266v1 Announce Type: cross Abstract: Agentic large language models (LLMs) now move money through tools, yet the record of what they did is usually a trace their own process emits beside t

LARC: Low-Rank Adaptive Residual Connections for Learning in Frozen Models

arXiv:2609.40063v1 Announce Type: cross Abstract: Low-Rank Adaptive Residual Connections (LARC) give a frozen model a compact numerical state that can learn from feedback. The map h+BAh adds a low-ran

Large Language Models are Approximate Survival Estimators

arXiv:2609.38181v1 Announce Type: new Abstract: Survival analysis estimates time-to-event outcomes from patient covariates and is widely used for medical risk assessment. Patients seeking prognostic i

Learning Reliable GUI Agents under Imperfect Priors

model-releasesarxiv-cs-lg

arXiv:2609.39547v1 Announce Type: new Abstract: GUI agents built on large language and vision-language models still struggle on unseen applications and complex multi-step tasks, as completing real GUI

Local-Minimum Escaper: Programmatic Subgoal Generation for Robust Navigation in Unknown Environments

arXiv:2609.38928v1 Announce Type: new Abstract: Mapless navigation in unknown and partially observable environments remains challenging for mobile robots, particularly when local minima prevent the ro

safetyarxiv-cs-ro

MASCRDM: Multi-Agent System for Compliance Risk Detection and Mitigation in Training Process of Large Language Models

arXiv:2609.39107v1 Announce Type: new Abstract: Large Language Models (LLMs) have been applied in various fields. However, ensuring compliance and safety of LLMs, such as avoiding discrimination and b

MedKIT: Evaluating Knowledge Integration and Generalization in Large Language Models

arXiv:2609.38543v1 Announce Type: new Abstract: Constantly evolving real-world knowledge necessitates models to be updated continuously. Especially in medicine, as clinical evidence changes over time,

MOBA-VL: Event-Localized Multi-Turn Reinforcement Learning for Real-Time MOBA Commentary

model-releasesarxiv-cs-cv

arXiv:2609.38428v1 Announce Type: new Abstract: Real-time commentary for Multiplayer Online Battle Arena (MOBA) esports requires a vision-language model (VLM) to narrate a live match second by second,

On the Off-Policy Teacher in On-Policy Distillation

arXiv:2609.38360v1 Announce Type: cross Abstract: On-policy distillation (OPD) has recently emerged as a promising post-training paradigm in which the student learns from trajectories generated by its

OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software

arXiv:2609.39903v1 Announce Type: new Abstract: Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires

Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

arXiv:2609.39975v1 Announce Type: cross Abstract: This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluati