Search: “reasoning”

When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?

model-releasesarxiv-cs-cl

arXiv:2503.23137v2 Announce Type: replace-cross Abstract: Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant c

16 Apr 2026

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Calibration-Aware Policy Optimization for Reasoning LLMs

DGX agent

arXiv:2604.12632v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) enhances LLM reasoning but often induces overconfidence, where incorrect responses yield lower perplexity th

safetyarxiv-cs-ai

15 Apr 2026

When Reasoning Models Hurt Behavioral Simulation: A Solver-Sampler Mismatch in Multi-Agent LLM Negotiation

model-releasesarxiv-cs-lg

arXiv:2604.11840v1 Announce Type: new Abstract: Large language models are increasingly used as agents in social, economic, and policy simulations. A common assumption is that stronger reasoning should

15 Apr 2026

A Progressive Training Strategy for Vision-Language Models to Counteract Spatio-Temporal Hallucinations in Embodied Reasoning

arXiv:2604.10506v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reason

Belief-Aware VLM Model for Human-like Reasoning

arXiv:2604.09686v1 Announce Type: new Abstract: Traditional neural network models for intent inference rely heavily on observable states and struggle to generalize across diverse tasks and dynamic env

LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models

arXiv:2604.09712v1 Announce Type: cross Abstract: Spatial reasoning is a cornerstone capability for intelligent systems to perceive and interact with the physical world. However, multimodal large lang

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2511.18373v2 Announce Type: replace Abstract: Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial

RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

arXiv:2604.11626v1 Announce Type: new Abstract: Most reward models for visual generation reduce rich human judgments to a single unexplained score, discarding the reasoning that underlies preference.

E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning

arXiv:2604.09455v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated significant potential in Tool-Integrated Reasoning (TIR), existing training paradigms face signific

Local Ai

Process Reward Agents for Steering Knowledge-Intensive Reasoning

arXiv:2604.09482v1 Announce Type: new Abstract: Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating ste

local-aiarxiv-cs-ai

Reasoning Provenance for Autonomous AI Agents: Structured Behavioral Analytics Beyond State Checkpoints and Execution Traces

arXiv:2603.21692v2 Announce Type: replace Abstract: As AI agents transition from human-supervised copilots to autonomous platform infrastructure, the ability to analyze their reasoning behavior across

Reinforcement-aware Knowledge Distillation for LLM Reasoning

arXiv:2602.22495v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) post-training has recently driven major gains in long chain-of-thought reasoning large language models (LLMs), but

Structuring versus Problematizing: How LLM-based Agents Scaffold Learning in Diagnostic Reasoning

arXiv:2604.09158v1 Announce Type: cross Abstract: Supporting students in developing diagnostic reasoning is a key challenge across educational domains. Novices often face cognitive biases such as prem

Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoning

arXiv:2604.08068v1 Announce Type: new Abstract: Decoding visual information from electroencephalography (EEG) has recently achieved promising results, primarily focusing on reconstructing two-dimensio

safetyarxiv-cs-cv

Enabling Intrinsic Reasoning over Dense Geospatial Embeddings with DFR-Gemma

model-releasesarxiv-cs-cl

arXiv:2604.07490v1 Announce Type: new Abstract: Representation learning for geospatial and spatio-temporal data plays a critical role in enabling general-purpose geospatial intelligence. Recent geospa

GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records

arXiv:2604.06684v1 Announce Type: new Abstract: Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in modern healthcare. While in-context learning (ICL) offer

applicationsarxiv-cs-lg

STRIDE-ED: A Strategy-Grounded Stepwise Reasoning Framework for Empathetic Dialogue Systems

arXiv:2604.07100v1 Announce Type: cross Abstract: Empathetic dialogue requires not only recognizing a user's emotional state but also making strategy-aware, context-sensitive decisions throughout resp

The Stepwise Informativeness Assumption: Why are Entropy Dynamics and Reasoning Correlated in LLMs?

arXiv:2604.06192v1 Announce Type: cross Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains largely em

CoTranslator: Reverse to Forward Chain-of-Thought Translator for Reasoning Distillation

arXiv:2610.20828v1 Announce Type: cross Abstract: Reasoning distillation requires chain-of-thought (CoT) data with correct answers, but obtaining such data efficiently remains challenging. Forward CoT

Evaluating Inquiry Learning in LLM-Based Agents: Hypothesizing, Reasoning, and Exploration

arXiv:2610.21604v1 Announce Type: new Abstract: Scientific inquiry involves iterative cycles of exploration, hypothesis generation, and reasoning over observations to uncover relationships in complex

LLM-as-an-Investigator: Evidence-First Agentic Reasoning for Robust Interactive Problem Diagnosis

arXiv:2606.13220v2 Announce Type: replace Abstract: Large language models (LLMs) are used for technical troubleshooting, where problem descriptions are often incomplete and multiple causes can explain

QREF: Improving DeepSearch Agents by Aligning Search with Reasoning via Query Refinement and Evidence Filtering

arXiv:2610.21512v1 Announce Type: new Abstract: DeepSearch agents achieve strong performance on complex information-seeking tasks through iterative search and reasoning. However, they often issue inte

applicationsarxiv-cs-ai

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-of

safetyarxiv-cs-cl

MolLean: A Process-Verifiable Language for Chemical Reasoning

arXiv:2610.20459v1 Announce Type: new Abstract: Chemical chain-of-thought can contain hallucinated structural and property claims. We thereby introduce MolLean, a process-verifiable language that grou

agentsarxiv-cs-cl

PsyMemBehav: Psychology-Informed and Memory-Grounded Two-Level Identity-to-Action Reasoning for Social-Media Behavior Simulation

arXiv:2610.14570v1 Announce Type: new Abstract: Large language models (LLMs) support social simulation, but faithfully reproducing real users requires grounding both structured platform decisions and

Towards a Data-Centric Understanding of Spatial Reasoning in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.19108v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been widely applied in embodied agents and robotics for vision tasks. However, MLLMs suffer from limitat

Tutorials

Anchors Enhance Controllability and Reasoning of Diffusion Language Models

arXiv:2610.15097v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer new opportunities for controllable text generation. However, their controllability, defined as the ability to sat

tutorialsarxiv-cs-lg

Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning

arXiv:2605.25437v2 Announce Type: replace Abstract: Visual reasoning through reinforcement learning with verifiable rewards (RLVR) has achieved remarkable progress. However, when dealing with multi-so

researcharxiv-cs-cv

Process Rewards for Outcome-Guided Reasoning Steps in LLM Reinforcement Learning

arXiv:2604.02341v2 Announce Type: replace Abstract: Mathematical reasoning in large language models has improved substantially with reinforcement learning using verifiable rewards, where final answers

safetyarxiv-cs-lg

SceneForesee: Learning Scene Evolution for Spatiotemporal Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.14439v1 Announce Type: new Abstract: Large multimodal models (LMMs) need to understand how entities move and interact as a scene develops. This requires following the same entities over tim

Enhancing Legal Reasoning in Pre-trained Language Models via Knowledge Graph-Guided Multi-Task Pre-training

arXiv:2610.13722v1 Announce Type: new Abstract: Legal language understanding requires reasoning over semi-structured regulatory documents, yet standard pre-training objectives do not explicitly target

applicationsarxiv-cs-cl

12 Oct 2026

Look Back, Think Ahead: Visual Memory on Demand for Efficient Multimodal Reasoning

arXiv:2610.12060v1 Announce Type: new Abstract: Processing long visual token sequences from high-resolution images makes multi-step reasoning computationally expensive for multimodal Large Language Mo

researcharxiv-cs-cv

9 Oct 2026

Think Before You Paint: Recursive Latent Reasoning for Diffusion Models

arXiv:2610.09876v1 Announce Type: cross Abstract: Diffusion models generate realistic images but often fail on visual reasoning tasks, such as filling in a Sudoku or drawing the path through a maze. W

researcharxiv-cs-lg

8 Oct 2026

Unrolled Flow Models for Reasoning

model-releasesarxiv-cs-lg

arXiv:2610.09759v1 Announce Type: new Abstract: Flow matching enables language generation in few steps, but whether additional integration steps improve reasoning remains unclear. We prove that a flow

8 Oct 2026

Hardware

YANchor-4B: Effective Long-Horizon Reasoning in O(N) Time with O(1) Memory

arXiv:2610.10118v1 Announce Type: cross Abstract: Long-horizon reasoning demands access to earlier information at a manageable generation cost. Full-history attention incurs growing storage and comput

hardwarearxiv-cs-cl

8 Oct 2026

Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence

arXiv:2610.07739v1 Announce Type: new Abstract: Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to dow

safetyarxiv-cs-lg

DHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning

arXiv:2610.07835v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orch

EgoLAP: Learning from Egocentric Human Data through Language-Action Reasoning

arXiv:2610.08726v1 Announce Type: cross Abstract: Egocentric human data offer a path to scaling robot learning beyond costly robot demonstrations, yet the embodiment gap makes raw human trajectories a

applicationsarxiv-cs-ai

FedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models

arXiv:2508.10020v2 Announce Type: replace-cross Abstract: Enhancing LLM reasoning in federated settings is nontrivial due to stringent computational, communication, and privacy constraints, especially

Incidental information contaminates patient notes and disrupts clinical reasoning in large language models

arXiv:2610.08585v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failu

researcharxiv-cs-cl

Test-Time Agent Evolution for Long-Horizon Legal Reasoning

arXiv:2610.08138v1 Announce Type: new Abstract: Legal intelligence aims to support reliable decision-making across long-horizon legal processes involving evolving case states and multiple roles. Howev

CyTReX: Explainable AI-Based Cybersecurity Threat Reasoning Framework for DER Networks

arXiv:2610.04286v1 Announce Type: cross Abstract: Distributed Energy Resource (DER) environments rely on network communication protocols to coordinate control commands, measurements, and device states

agentsarxiv-cs-lg

Local Ai

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

arXiv:2610.05023v1 Announce Type: new Abstract: We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image r

local-aiarxiv-cs-cv

SpatialChain: A Benchmark for Auditing Spatial Reasoning Faithfulness in VLMs

model-releasesarxiv-cs-cv

arXiv:2610.06413v1 Announce Type: new Abstract: Thinking-enabled vision-language models (VLMs) report ever-higher accuracy on spatial benchmarks, yet final-answer scores cannot reveal whether a correc

Transfer-Stratified On-Policy Distillation for RL-Improved Reasoning Teachers

arXiv:2610.05974v1 Announce Type: new Abstract: Reinforcement learning can substantially improve a reasoning teacher, but it is unclear which of those improvements survive when the teacher supervises

safetyarxiv-cs-lg

Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA

arXiv:2610.05025v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist

researcharxiv-cs-cv

Learning What to Investigate Next: Meta-Reasoning for Long-Horizon Research Agents

arXiv:2610.02525v1 Announce Type: new Abstract: Long-horizon research agents must decide both how to investigate and what to investigate next as evidence accumulates. This is hard to learn because suc

5 Oct 2026

Preserving Mathematical Reasoning in Compressed Diffusion Language Models via Trajectory-Aware Low-Rank Approximation

arXiv:2610.03326v1 Announce Type: new Abstract: Diffusion language model (dLLM) compression faces a known challenge because calibration is typically performed on clean, fully visible activations, wher