Search: “reasoning”

Skill Issue: Are Skills Language-Invariant in LLMs?

model-releasesarxiv-cs-cl

arXiv:2608.25832v1 Announce Type: new Abstract: Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with diff

27 Aug 2026

TTSR: Test-Time Self-Evolving via Reflection

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DGX agent

arXiv:2603.03297v2 Announce Type: replace Abstract: Test-time training (TTT) adapts large language models (LLMs) during inference using only unlabeled test inputs. Existing methods, however, face two

tutorialsarxiv-cs-cl

27 Aug 2026

Beyond Confidence: Test-Time Scaling for Multi-Turn Search Agents via Retrieval Grounding

arXiv:2608.24024v1 Announce Type: new Abstract: Confidence-based voting aggregates parallel LLM rollouts by weighting each with internal signals such as token log probabilities, and has been actively

26 Aug 2026

Function-Level Execution Feedback for Code Preference Optimization

arXiv:2608.23632v1 Announce Type: new Abstract: Process supervision has improved mathematical reasoning, where intermediate steps are naturally expressed as chains of thought. In code generation, howe

26 Aug 2026

DIAG: Diagnostic Iterative Alignment and Generation for Data-Efficient Mathematical Preference Distillation

arXiv:2608.22806v1 Announce Type: new Abstract: Iterative preference optimization is essential for aligning Large Language Models on mathematical reasoning tasks, yet its efficiency is often throttled

Perturb the Thought, Not the Pixels: Latent-Space Rollout Diversification for Reinforcement Learning of Vision-Language Models

arXiv:2608.21595v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning ability of vision-language models (VLMs), and diversifying the rollouts wit

safetyarxiv-cs-cv

Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding

arXiv:2608.22429v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) capable of thinking with images often rely on external tools for fine-grained perception. However, this relianc

Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs

arXiv:2608.22854v1 Announce Type: new Abstract: Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style mod

safetyarxiv-cs-lg

A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans

arXiv:2608.21140v1 Announce Type: cross Abstract: Reliable spatial understanding is an important prerequisite for future medical vision-language systems that aim to support radiological report generat

A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

arXiv:2608.20379v1 Announce Type: new Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agen

ForeDreamer: A Self-Evolving Dual-Agent Memory Architecture for Future Event Prediction

arXiv:2608.20920v1 Announce Type: new Abstract: Open-web future event prediction requires agents to distill reliable signals from noisy, redundant, and incomplete evidence. Existing retrieval/memory m

agentsarxiv-cs-cl

Volumetric Radiology AI in the Era of Multimodal Large Language Models

arXiv:2608.20549v1 Announce Type: new Abstract: Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward

safetyarxiv-cs-ai

Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation

arXiv:2608.20316v1 Announce Type: new Abstract: Heterogeneous AI systems composed of multiple models, architectures, harnesses, or inference-time settings can improve quality and efficiency by routing

21 Aug 2026

TempJail: Temporal Jailbreak Attack against Large Vision-Language Models via Subtitle Scheduling

arXiv:2608.19737v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have achieved remarkable progress in video understanding and reasoning. Despite extensive studies on text- and im

21 Aug 2026

DeepTCM1.0: A Multi-Expert AI Agent for Deciphering Mechanisms of Chinese Herbal Formulae Based on General Large Language Models

arXiv:2608.18103v1 Announce Type: cross Abstract: Background: Mechanistic elucidation of traditional Chinese medicine (TCM) compound formulas remains a central challenge in the modernization of TCM. C

RDFdL: Integrating RDF with Differential Dynamic Logic

arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s

safetyarxiv-cs-ai

RTPO: Reverse-Turn Policy Optimization for Stabilizing Agentic RL Training

arXiv:2608.18682v1 Announce Type: new Abstract: Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, a

safetyarxiv-cs-ai

When Safety Overrides Vision: Exploring Dynamics between Vision Influence and Safety Alignment in Vision-Language Models

arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking

Applications

CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method

arXiv:2608.17536v1 Announce Type: cross Abstract: Legal consultation questions exhibit multi-level complexity. A single retrieval strategy often leads to over-reasoning for simple questions and poor i

applicationsarxiv-cs-ai

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

arXiv:2608.17950v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable multi-hop reasoning capabilities over long contexts, yet the internal mechanisms enabling these dist

researcharxiv-cs-cl

GroupForward: Building Referable 3D Scenes via Instance-Grouped Feed-Forward Gaussian Splatting

arXiv:2608.17535v1 Announce Type: new Abstract: Simultaneously reconstructing and understanding 3D environments is essential for embodied agents. Toward this goal, feed-forward semantic 3D Gaussian Sp

researcharxiv-cs-cv

MCTS-KBQA: Monte Carlo Tree Search with Information Gain Rewards for Knowledge Base Question Answering

arXiv:2502.13428v2 Announce Type: replace-cross Abstract: This work investigates how to improve large language model (LLM)-based reasoning for knowledge base question answering (KBQA) via Monte Carlo

tutorialsarxiv-cs-ai

Neuro-symbolic learning over OWL 2 DL via consequence-based compilation to differentiable circuits

arXiv:2608.17741v1 Announce Type: new Abstract: OWL 2 DL ontologies, grounded in the description logic SROIQ, express large knowledge bases in biomedicine and the Semantic Web. Neuro-symbolic (NeSy) l

PROBE: Manipulation-Grounded Visual Question Answering with VLM Agents

arXiv:2608.17129v1 Announce Type: new Abstract: Vision-language Models (VLMs) excel at 2D grounding, spatial reasoning and agentic tool-based planning in static scenes. However, consider asking a home

agentsarxiv-cs-cv

Euclid-Omni : A Unified Neuro-Symbolic Framework for Plane Geometry

arXiv:2608.14585v1 Announce Type: new Abstract: Euclidean geometry is a compelling testbed for AI reasoning, as it demands the combination of intuitive diagram understanding, axiomatic deduction, and

HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation

arXiv:2608.15703v1 Announce Type: new Abstract: Large language model (LLM) agents often perform poorly on complex, long-horizon tasks because their context becomes increasingly cluttered over time. As

Language Models that Think, Chat Better

model-releasesarxiv-cs-cl

arXiv:2509.20357v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) trains language models to use long chain-of-thought reasoning (CoT) in domains like mathematic

Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization

arXiv:2608.16072v1 Announce Type: cross Abstract: Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training language model reasoners. However, when

GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings

arXiv:2608.13698v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), often optimized with Group Relative Policy Optimization (GRPO), has become a central recipe for i

P2Skill: Privacy Preserving Skill Distillation for Cloud-Local LLM Inference Systems

arXiv:2608.14094v1 Announce Type: cross Abstract: Cloud-local LLM inference systems have the potential to use the reasoning capability of large cloud models while protecting sensitive user data on per

Research-Oriented Human-Centric Evaluation for Foundation Models

arXiv:2506.01793v2 Announce Type: replace Abstract: Most current evaluations of foundation models focus on objective benchmarks, such as knowledge coverage and reasoning accuracy, often overlooking us

researcharxiv-cs-cl

Rewrite Once, Validate Anywhere: Producing OWL-Aware SHACL Constraints (Extended Version)

arXiv:2608.14104v1 Announce Type: cross Abstract: The Shapes Constraint Language (SHACL) is a W3C recommendation to express syntactic constraints, called shapes, on RDF graphs. SHACL validators are us

Rollplex: Cross-Phase GPU Spatial Sharing for Vision Language Model Post-Training

model-releasesarxiv-cs-lg

arXiv:2608.14498v1 Announce Type: new Abstract: Vision-language models (VLMs) enable embodied agents to reason and act from visual observations and language instructions. Reinforcement learning (RL) p

Edit2TikZ: A Comprehensive and Challenging Benchmark for Scientific Figure Editing with TikZ

model-releasesarxiv-cs-cv

arXiv:2608.13441v1 Announce Type: new Abstract: Although multimodal large language models (MLLMs) have shown substantial potential in visual understanding and graphic code generation, editing scientif

EgoMonth: A Month-Level Egocentric Video Benchmark for Long-Term Spatiotemporal Memory

arXiv:2608.13113v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to substantial progress in video understanding, accompanied by a growing number o

Hardware

Enhancing Virtual Agents through SLMs and Edge-Computing: An Exploratory Evaluation of Think and Memory Processes

arXiv:2608.13420v1 Announce Type: new Abstract: Embodied intelligent virtual agents are expected to operate as persistent, adaptive, and context-aware entities within complex virtual and Metaverse wor

hardwarearxiv-cs-ai

EviReform: Evidence-Guided Query Reformulation for Multi-Hop Graph Retrieval

arXiv:2608.13006v1 Announce Type: new Abstract: Multi-hop retrieval must recover passages that provide sufficient evidence together. An initial passage often resolves an entity or relation implicit in

tutorialsarxiv-cs-cl

PROVE-RT: Generating Mechanized Theorem Prover Scripts for Real-Time Systems using LLMs

arXiv:2608.12762v1 Announce Type: new Abstract: Schedulability analysis is essential for certifying real-time systems, but existing tests are often developed through pen-and-paper proofs that are diff

Social Chain of Thought: A Multi-Agent Architecture Grounded in Medical Differential Diagnosis Methodology

arXiv:2608.11420v1 Announce Type: new Abstract: Medical diagnostic reasoning is a high-impact use case for LLMs that carries significant implications for the health and wellbeing of users. When OpenAI

13 Aug 2026

Applications

Social Meaning in Large Language Models: Structure, Magnitude, and Pragmatic Prompting

arXiv:2604.02512v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly exhibit human-like patterns of pragmatic and social reasoning. This paper addresses two related ques

applicationsarxiv-cs-ai

13 Aug 2026

Towards Understanding On-Policy Distillation through the Lens of Test-Time Scaling

arXiv:2608.11829v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as a promising post-training technique for enhancing LLM reasoning. It is commonly believed to enable the stu

13 Aug 2026

FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation

arXiv:2608.10916v1 Announce Type: cross Abstract: Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to asses

Is This Your Final Answer? Cross-Contextual Consistency as a Measure of LLM Credibility

arXiv:2608.10315v1 Announce Type: cross Abstract: Large language models (LLMs) are powerful black-box systems, making it difficult to discern whether their answers reflect stable internal beliefs or s

Rationale-Guided Learning for Multimodal Emotion Recognition

arXiv:2608.10448v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (MERC) requires understanding complex interactions between verbal and non-verbal cues. However, most exis

tutorialsarxiv-cs-ai

Surfacing the Unsaid: CUE-Bench for Affective Stance in Chinese Discourse

arXiv:2608.10810v1 Announce Type: cross Abstract: Emotion understanding in discourse requires reasoning beyond surface sentiment because speakers often convey affect through indirect, implicit, polite

360CityArena: A Realistic Virtual Urban Navigation Benchmark for Embodied Agents

arXiv:2608.08814v1 Announce Type: cross Abstract: We present 360CityArena, a benchmark for evaluating the urban exploration capabilities of embodied agents within a photorealistic environment construc

11 Aug 2026

Agent-MD: Selective LLM Intervention with Event-Driven Escalation for Stateful GCMC--MD Campaigns

arXiv:2608.07637v1 Announce Type: new Abstract: Long-running molecular simulation campaigns require repeated continuation from saved states, provenance-aware progression, adaptive assessment, and occa

11 Aug 2026

Applications

Exploring LLM Capabilities for Situational Understanding and COLREG compliance on real-world maritime navigation scenarios