Search: “reasoning”

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

arXiv:2608.08764v1 Announce Type: cross Abstract: On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a

11 Aug 2026

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Research

Quality-Diversity Stress Tests for Process Reward Models:What Archive Coverage Can and Cannot Certify

DGX agent

arXiv:2608.08008v1 Announce Type: new Abstract: Process reward models (PRMs) score intermediate reasoning steps and are widely used for search, ranking, and training, but optimization can exploit thes

researcharxiv-cs-lg

11 Aug 2026

When Counterbalancing Hides the Bias: Access-Conditioned Position Lock in Forced-Choice LLM Evaluation

arXiv:2607.10202v2 Announce Type: replace Abstract: Forced-choice probes with counterbalanced orientations are a standard tool for measuring language-model 'value dispositions,' and a concentration/ex

11 Aug 2026

Pre-Inference Routing for Cost-Efficient Document Field Extraction

arXiv:2608.06607v1 Announce Type: new Abstract: Most document-extraction systems use a single model for all documents. This is simple but can be costly for easy cases and less effective for difficult

researcharxiv-cs-cl

10 Aug 2026

Recovering Explanations from Transformed Rule-Based Ontologies

arXiv:2608.06399v1 Announce Type: cross Abstract: Datalog rules are often used to define ontologies over Knowledge Graphs. Rule reasoners routinely optimise such ontologies by rewriting their rules in

researcharxiv-cs-ai

10 Aug 2026

Social World Models

arXiv:2509.00559v3 Announce Type: replace Abstract: Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited informat

10 Aug 2026

M^3R-Bench: A Unified Benchmark for Evidence-Grounded Multimodal Metaphor Understanding

arXiv:2608.05817v1 Announce Type: new Abstract: Metaphor enables the understanding of abstract concepts through cross-domain mappings while conveying affective attitudes. In multimodal scenarios, visu

7 Aug 2026

Tutorials

STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts

arXiv:2602.14265v3 Announce Type: replace Abstract: Inference-Time-Compute (ITC) methods like Best-of-n and Tree-of-Thoughts are meant to produce output candidates that are both high-quality and diver

tutorialsarxiv-cs-cl

7 Aug 2026

DAC-Pose: Dual-Agent Collaborative Framework for Pose-Guided Human Generation

arXiv:2608.04622v1 Announce Type: new Abstract: AI agents have emerged as a powerful new paradigm in generative image synthesis, enabling systems to perform complex semantic reasoning rather than pass

safetyarxiv-cs-cv

6 Aug 2026

Same Formulas, Different Semantics: Do Language Models Follow Modal Logic Specifications?

arXiv:2608.05097v1 Announce Type: new Abstract: Reasoning about necessity and possibility depends on assumptions about accessibility between worlds and about which objects exist at each one. The same

6 Aug 2026

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding

arXiv:2608.05137v1 Announce Type: new Abstract: Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, incl

6 Aug 2026

BODHI: Do LLMs Branch Out and Discover Heterogeneous Inferences?

arXiv:2608.02867v1 Announce Type: cross Abstract: Although reinforcement learning with verifiable rewards (RLVR) has improved the performance of large language models (LLMs) across a variety of reason

Don't Peek at the Answer: Outcome-Masked Group Relative Policy Optimization for Label-Free RLVR

arXiv:2608.03119v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves LLM reasoning but typically relies on ground-truth (GT) answers, limiting scalability. Vo

GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits

arXiv:2608.02877v1 Announce Type: new Abstract: Causal discovery recovers directed structure from observational data and is increasingly used in clinical settings to support mechanism reasoning and fa

Interpretable Adaptive Sampling for LLM Test-Time Scaling

arXiv:2608.03961v1 Announce Type: new Abstract: Test-time scaling improves LLM reasoning by generating and aggregating multiple candidate answers, yet many pipelines use fixed per-query budgets that s

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding

arXiv:2607.17999v2 Announce Type: replace-cross Abstract: Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic informatio

Don't Judge a Book by its Cover: Testing LLMs' Robustness Under Logical Obfuscation

arXiv:2602.01132v2 Announce Type: replace Abstract: Tasks such as solving arithmetic equations, evaluating truth tables, and completing syllogisms are handled well by large language models (LLMs) in t

Image-Space Rule Discovery

arXiv:2608.00490v1 Announce Type: new Abstract: Can image-editing models discover visual rules in image space and complete problem-solving end-to-end? We tackle this question in the spirit of a human

MonitorVLM-v2: A Deployed Vision-Language Framework for Real-Time Safety Violation Detection

arXiv:2608.00975v1 Announce Type: new Abstract: Large vision--language models (VLMs) can reason step by step about complex visual scenes, but this open-ended, autoregressive chain-of-thought (CoT) app

safetyarxiv-cs-cv

STAR-VLM: Spatiotemporal Grounding Vision-Language Models for Motion and Velocity Estimation via Automotive Radar Supervision

arXiv:2608.01535v1 Announce Type: new Abstract: Vision-language models (VLMs) are emerging as a key component of embodied intelligence, with growing applications in auto-labeling and end-to-end autono

agentsarxiv-cs-cv

AMTFV: Agentic Mathematical Tool-Flow Verification for LLM Self-Correction

arXiv:2607.29549v1 Announce Type: new Abstract: Large language models have demonstrated strong mathematical problem-solving capabilities, yet reliably verifying their candidate answers remains challen

3 Aug 2026

Tokenizer-Agnostic Engram Module

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

3 Aug 2026

Tutorials

TransMem: Transforming Hidden States into Memory for Large Language Models

arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting

tutorialsarxiv-cs-cl

3 Aug 2026

Compliance2LoRA: On-Demand Safety Alignment on Arbitrary Policy Subsets via Hypernetwork-Generated LoRA Adapters

arXiv:2607.27594v1 Announce Type: new Abstract: Post-training alignment in large reasoning models (LRMs) has significantly improved their adaptability to diverse safety compliance settings. However, a

safetyarxiv-cs-lg

Divergence Decoding: Training-Free Capability Fusion

arXiv:2607.27248v1 Announce Type: cross Abstract: While large language models excel in reasoning, these generalists often lack knowledge for specialized scientific domains. Conversely, domain models~(

GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation

arXiv:2602.14649v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit strong reasoning abilities, but their high computational costs limit their practical deployment. Recent studies

researcharxiv-cs-cl

Hand-Object Interaction in the Age of Large Foundation Models:Reconstruction, Generation, and Embodied Transfer

arXiv:2607.28394v1 Announce Type: new Abstract: Hand-object interaction (HOI) modeling remains challenging because it requires joint reasoning about hand articulation, object geometry, contact, semant

researcharxiv-cs-cv

LoMeVQA: A Comprehensive Benchmark for Longitudinal Medical VQA

arXiv:2607.27806v1 Announce Type: new Abstract: In clinical practice, patients often undergo multiple imaging examinations over successive visits, yielding longitudinal data. Modeling such temporal in

LoRA Scaffolded Policy Optimization (LSPO): A Sampling-Time Low-Rank Scaffold for Recovering Reinforcement-Learning Gradient on Zero-Reward Cliff Prompts

arXiv:2607.27787v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) for mathematical reasoning suffers from a structural blind spot: on 'cliff' prompts-those on which

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory

arXiv:2607.27919v1 Announce Type: new Abstract: Decoder-only language models entangle long-term memory and reasoning in a single parameter set, making it difficult to scale memory capacity independent

Beyond Memory: A Templated Substrate for Heterogeneous Collaborative Knowledge Work with LLM Agents

arXiv:2607.24759v1 Announce Type: new Abstract: Research projects, educational efforts, and adjacent knowledge work accumulate findings, decisions, and reasoning that future collaborators rarely recov

agentsarxiv-cs-ai

29 Jul 2026

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model

arXiv:2607.24904v1 Announce Type: cross Abstract: Standard vision-language models (VLMs) suffer from Moravec's paradox: they excel at complex offline visual reasoning but struggle with simple streamin

29 Jul 2026

SearchArt: Training Long-Horizon Search Agent with Scalable Synthetic and Verified Task

arXiv:2607.24850v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled search agents to autonomously tackle complex tasks across extended search and reasoning h

safetyarxiv-cs-lg

29 Jul 2026

Aligning Quantum Operators with Large Language Models

arXiv:2606.13811v2 Announce Type: replace-cross Abstract: Can Large Language Models (LLMs) understand and reason about quantum operators? Despite their remarkable capabilities in mathematics and symbo

researcharxiv-cs-ai

Confidently Wrong: Exception Chain Collapse in Frontier LLM Rule Evaluation

arXiv:2607.23386v1 Announce Type: new Abstract: We document a failure class in frontier large language models -- exception chain collapse -- observed in eligibility evaluation under nested conditional

Evaluating Large Language Models for Symbolic Security Protocol Analysis

arXiv:2607.20712v1 Announce Type: cross Abstract: Security protocol verification relies on formal tools such as ProVerif and OFMC. This study evaluates whether Large Language Models (LLMs) can perform

Applications

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

arXiv:2607.24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to under

applicationsarxiv-cs-ai

Focus Is All You Need: Adaptive Goal-aware Attention Orchestration for Multi-Agent Graph Systems

arXiv:2607.23678v1 Announce Type: new Abstract: Large language models (LLMs) enable autonomous agents for reasoning, planning, and tool use. Recent systems increasingly organize these agents as graphs

agentsarxiv-cs-ai

HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering

arXiv:2607.22597v1 Announce Type: new Abstract: Multi-hop question answering requires systems to retrieve evidence from multiple documents and connect scattered facts into a coherent reasoning process

researcharxiv-cs-ai

Multi-Objective Structured Pruning of LLMs for Latency and Model Size Optimization

arXiv:2607.22583v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved widespread adoption because of their strong reasoning and query-response capabilities. However, deploying the

Hardware

Spatial-IQ: Deconstructing Spatial Intelligence via Hierarchical Capability Tests

arXiv:2607.22864v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) excel at visual interpretation but fail on spatial reasoning tasks that humans solve reliably. Existing bench

hardwarearxiv-cs-ai

Stress-testing large language model agents in a robotic chemistry laboratory

arXiv:2607.23045v1 Announce Type: new Abstract: AI is evaluated through knowledge, reasoning and plan generation, yet scientific agency requires reliable physical action and adaptation to evidence. He

agentsarxiv-cs-ai

From Isolated Tasks to Structured Capabilities: A Multilayer Taxonomy for Large Language Models

arXiv:2607.22182v1 Announce Type: new Abstract: Large language model (LLM) evaluation spans diverse tasks and benchmarks, yet evidence remains organized around tasks rather than the capabilities they

researcharxiv-cs-cl

27 Jul 2026

AI Assistants Overassist

arXiv:2607.21306v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems. While guidance from AI assis

24 Jul 2026

SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration

arXiv:2607.20926v1 Announce Type: new Abstract: Scientific research involves complex information-seeking and reasoning workflows across heterogeneous sources. However, existing benchmarks primarily em

24 Jul 2026

Local Ai

Test-Time Scaling via Error Localization

arXiv:2607.21453v1 Announce Type: new Abstract: Scaling inference-time computation has emerged as a reliable method to improve the performance of large language models on complex reasoning and program

local-aiarxiv-cs-lg

24 Jul 2026

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection

arXiv:2512.16300v3 Announce Type: replace Abstract: Existing image forgery detection (IFD) methods either exploit low-level, semantics-agnostic artifacts or rely on multimodal large language models (M