Search: “reasoning”

Beyond Information Retrieval: Generative AI as an Epistemic Arbiter to Enhance Collaborative Problem-Solving

arXiv:2608.05171v1 Announce Type: cross Abstract: Generative AI (GAI) creates new opportunities for collaborative problem-solving (CPS), yet its role in shaping student interaction remains unclear. To

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From Passive Mirrors to Active Agents: Holonic Digital Twins for Physical AI over Networks

DGX agent

arXiv:2608.06227v1 Announce Type: cross Abstract: Despite advances in artificial intelligence (AI) across multiple sectors, today's AI tools, including deep learning and generative AI, still fail when

local-aiarxiv-cs-ai

7 Aug 2026

In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use

arXiv:2608.05738v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become the dominant recipe for generalist manipulation, yet they are almost universally trained by behavior clo

safetyarxiv-cs-ro

Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval

arXiv:2608.06060v1 Announce Type: new Abstract: Unified multimodal retrieval aims to identify candidates that satisfy complex user intent expressed through heterogeneous inputs. Although Large Vision-

MoCA: Implicit Social Context Analysis

arXiv:2608.05825v1 Announce Type: new Abstract: Human social communication, such as affection and intent, is often conveyed in highly implicit ways, where underlying meanings are expressed through ind

NeSy-RAG: Neuro-Symbolic RAG for Explainable Question Answering

arXiv:2608.06292v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves question answering by grounding large language models (LLMs) in external knowledge such as text corpora. H

Neuro-Symbolic Closed-Loop Control of Laser Powder Bed Fusion with an In-Loop Ontology

model-releasesarxiv-cs-lg

arXiv:2608.05773v1 Announce Type: new Abstract: A geometry-conditioned, neuro-symbolic closed-loop architecture is proposed for laser powder bed fusion, in which a standards-aligned ontology operates

OmniMech: All-in-one Multimodal Mechanical Benchmark for 3D Reconstruction

arXiv:2608.05539v1 Announce Type: new Abstract: Recent vision-language models (VLMs) can generate executable CAD programs from images, but existing methods mainly target coarse, general-purpose 3D obj

Local Ai

Prior-SG: Task and Prior Driven Region Segmentation for Scene Graphs in Arbitrarily-Structured Environments

arXiv:2608.06170v1 Announce Type: cross Abstract: Hierarchical 3D scene graphs are a promising representation for high-level spatial reasoning in autonomous mobile platforms. However, existing extract

local-aiarxiv-cs-cv

SCP-NL2TL: Selective Conformal Prediction with Semantic Verification for Natural Language to Temporal Logic Specifications

arXiv:2608.05439v1 Announce Type: new Abstract: Translating natural language instructions into machine-interpretable formal specifications enables robots and autonomous systems to plan, reason, and fo

safetyarxiv-cs-ai

SearchAuditor: Auditing and Attributing Failures in Long-Horizon Search Agents

arXiv:2608.05212v1 Announce Type: new Abstract: Deep search agents tackle challenging questions through long-horizon web interactions, a process that is both complex and fragile: small reasoning error

Visual Intention Grounding for Egocentric Assistants

arXiv:2504.13621v2 Announce Type: replace Abstract: Visual grounding associates textual descriptions with objects in an image. Conventional methods target third-person image inputs and named object qu

Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settings

arXiv:2608.04735v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is increasingly treated as an important safety layer for frontier reasoning models. Most monitorability evaluations st

On The Suitability of Differential Dataflow For Datalog Interpretation In Highly Dynamic Settings

arXiv:2308.04214v2 Announce Type: replace-cross Abstract: In the domain of knowledge representation and reasoning within AI, datalog engines play an ever-increasingly crucial role. The crux of their o

researcharxiv-cs-ai

Plus and Pro users can access the updated version of GPT‑5.6 Sol in ChatGPT along with the new slider starting today. This version of GPT-5.…

Plus and Pro users can access the updated version of GPT‑5.6 Sol in ChatGPT along with the new slider starting today. This version of GPT-5.6 Sol is for everyday chats, so it will only be available in

model-releasesopenai--x

Privileged, but Biased: How PI-Conditioned Teachers Break Self-Distillation

arXiv:2608.04794v1 Announce Type: new Abstract: Self-distillation (SD) has emerged as a compute-efficient alternative to reinforcement learning with verifiable rewards: a self-teacher, conditioned on

safetyarxiv-cs-ai

RUTA: Principled Visual Token Allocation via Rate-Utility Optimization

arXiv:2608.04132v1 Announce Type: new Abstract: High-resolution images and long videos provide vision-language models with rich context for multimodal reasoning and fine-grained perception, but the re

The new GPT-5.6 Sol powers all chats for paid users, including Instant, creating one consistent experience. In our high-stakes factuality ev…

The new GPT-5.6 Sol powers all chats for paid users, including Instant, creating one consistent experience. In our high-stakes factuality evaluation covering finance, medicine and law, the new GPT‑5.6

model-releasesopenai--x

When Modalities Remember: Continual Learning for Multimodal Knowledge Graphs

arXiv:2604.02778v2 Announce Type: replace Abstract: Real-world multimodal knowledge graphs (MMKGs) are dynamic, with new entities, relations, and multimodal knowledge emerging over time. Existing cont

ANCHOR-RE: An Agentic Neuro-Symbolic Framework for Grounded Biomedical Relation Extraction

arXiv:2608.03154v1 Announce Type: new Abstract: Biomedical relation extraction (BioRE) extracts structured knowledge from biomedical literature for applications such as knowledge base construction and

Better, Stronger, Faster, and Broader: Structured All-Mask Prediction for MLLM-Based Segmentation

arXiv:2608.02791v1 Announce Type: new Abstract: MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-pre

Local Ai

DiagLoop: A Counterfactual Data Flywheel with Stage-Localized Reinforcement for Diagnostic LLMs

arXiv:2608.03674v1 Announce Type: new Abstract: Causal diagnostic models must explain how conclusions follow from evidence because diagnoses guide repairs and treatments. Yet serious cases are scarce,

local-aiarxiv-cs-lg

GENESIS: Towards Explainable Causal Discovery

arXiv:2608.03868v1 Announce Type: cross Abstract: Causal Discovery (CD) from observational data faces two fundamental challenges. First, purely statistical methods often lack the power to resolve stru

Hi-TTRL: Regulating Consensus with Hints for Test-Time Reinforcement Learning

arXiv:2608.03545v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) improves the reasoning capabilities of large language models without labeled data by updating the policy with ps

Hybrid LLM-Augmented Reinforcement Learning Agents for Complex Sequential Decision Tasks

arXiv:2608.03502v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently shown strong capabilities in reasoning, planning, and tool-use, enabling new forms of autonomous agents. Howe

agentsarxiv-cs-ai

MAFIA: Query-Only Memory Attacks via Probing and Factual Injection against Audited LLM Agents

arXiv:2608.03844v1 Announce Type: new Abstract: Memory-augmented LLM agents rely on rich context for long-horizon reasoning and acting, yet their memory modules expose a persistent attack surface for

agentsarxiv-cs-ai

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis

arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs

arXiv:2608.03573v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) exhibit fundamentally different behaviors in enhancing multi-task reasoning for large langu

TARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents

arXiv:2608.03699v1 Announce Type: new Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existin

Towards Improving Sequential Decision-Making in LLM Agents via Experience Memory

arXiv:2608.03420v1 Announce Type: new Abstract: Large language models have improved substantially on single-shot reasoning tasks, but their performance in sequential decision-making is less well under

agentsarxiv-cs-ai

UHP Detection: LVLMs have their Unique Hallucination Pattern in the Consistency Space

arXiv:2608.03817v1 Announce Type: cross Abstract: Large vision--language models (LVLMs) demonstrate strong multimodal reasoning capabilities but remain prone to hallucination, where model predictions

researcharxiv-cs-ai

Averaging Bias: Human Faithfulness Annotations are not Locally Faithful

arXiv:2608.00205v1 Announce Type: new Abstract: Evaluation of faithfulness of text summarization treats a model generated summary as faithful only if every of its sentences is supported by the source

CrossProjection: Geometric Grounding Beyond Viewpoint Change in Architectural Drawings

arXiv:2608.00473v1 Announce Type: cross Abstract: Architectural drawings violate the usual assumption behind multi-view reasoning: plans and sections are cuts, while elevations are facade projections,

Deep Research Pretraining via Predictive Navigation

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

Emergence Invariance: From Symbolized Thought to Interface Refinement

model-releasesarxiv-cs-lg

arXiv:2608.01548v1 Announce Type: cross Abstract: Language can be viewed as a formalized subset of thought: a consequence-governed symbolic structure projected from wider situated cognition. Large lan

Evaluating VLMs on Multimodal Aristotelian Persuasion Tasks

arXiv:2608.01238v1 Announce Type: new Abstract: Vision Language Models (VLMs) have demonstrated exceptional performance across various tasks. However, they have not yet been thoroughly evaluated on mo

HarnessCompass: Guiding Automatic Harness Evolution toward Generalizable and Effective Agent Harnesses

arXiv:2608.01918v1 Announce Type: cross Abstract: Harness design plays a critical role in agent performance by shaping how large language models (LLMs) perceive, reason over, and act within executable

It's the Decoding Format, Not the Perturbation: Auditing Consistency-Based Selection for Vision-Language Test-Time Scaling

arXiv:2608.01207v1 Announce Type: new Abstract: Test-time scaling lifts large language model reasoning by sampling many candidate solutions and selecting among them, yet the same recipe transfers poor

Just on Time: Token-Level Early Stopping for Diffusion Language Models

arXiv:2602.11133v2 Announce Type: replace-cross Abstract: Diffusion language models generate text through iterative refinement, a process that is often computationally inefficient because many tokens

researcharxiv-cs-cl

Latency-Tolerant Cloud-Edge Collaborative Vision-Language-Action Models via Emergent Representational Specialization

model-releasesarxiv-cs-ro

arXiv:2608.00569v1 Announce Type: new Abstract: Deploying billion-parameter Vision-Language-Action (VLA) policies on mobile robots creates a systems conflict: semantic reasoning benefits from cloud GP

Learning Compositional Meta-Routing for Agentic Workflows: An Executable Benchmark

model-releasesarxiv-cs-lg

arXiv:2608.00106v1 Announce Type: new Abstract: Agentic systems must decide not only what answer to produce, but which reasoning and execution operations should precede it. A controller may answer dir

LongHorizon-Harness: Advancing Long-Horizon Agents for Real-World Tasks

arXiv:2608.01964v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly undertake long-horizon tasks that require sustained reasoning, tool use, and revision across many interde

Hardware

NVIDIA Alpamayo 2 Super, the Frontier Open Model for Robotaxis and Autonomous Vehicles, Now Available for Commercial Use

For robotaxis and other autonomous vehicles (AVs), the hardest problems aren’t the everyday scenarios. They’re the rare, complex situations that are difficult to anticipate and train for. Handling the

hardwarenvidia-blog

On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generation

arXiv:2602.06423v2 Announce Type: replace Abstract: Humor is a commonly used and intricate human language in daily life. Humor generation, especially in multi-modal scenarios, is a challenging task fo

researcharxiv-cs-cl

Local Ai

PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding

arXiv:2601.02457v2 Announce Type: replace Abstract: Current foundation models for 3D shapes excel at global tasks (retrieval, classification) but transfer poorly to local part-level reasoning. Recent

local-aiarxiv-cs-cv

Practical Online KV Cache Compaction for LLM Agents: An Empirical Study

arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV c

agentsarxiv-cs-cl

SIEVE: Selective Integrity Verification and Escalation for Defending LLM Agents against Indirect Prompt Injection

arXiv:2512.06716v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used as the core of agentic systems due to their strong reasoning, planning, and tool-use capabi

agentsarxiv-cs-cl

Trustworthiness Costs of Domain Adaptation in Small Language Models:A Cross-Architecture Empirical Study

arXiv:2608.00042v1 Announce Type: new Abstract: Domain adaptation of small language models (SLMs) has emerged as a practical strategy for deploying capable NLP systems in resource-constrained, high-st