Search: “reasoning”

arXiv:2609.03931v1 Announce Type: new Abstract: Generating complete 3D scenes from sparse, unconstrained views is a fundamental challenge in 3D vision which requires reasoning beyond observed content

tutorialsarxiv-cs-cv

4 Sept 2026

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Automated Maize Ear Phenotyping Using 3D Reconstructions

DGX agent

arXiv:2609.01921v1 Announce Type: new Abstract: Maize kernel traits such as row number, kernels per row, and kernel size vary largely for genetic reasons and are consistently associated with regions o

researcharxiv-cs-cv

3 Sept 2026

Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems

arXiv:2609.02750v1 Announce Type: new Abstract: Multi-agent LLM systems commonly use an orchestrator to decompose a task for a team of workers and then improve through textual reflection. Despite stro

CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluation

arXiv:2602.12639v2 Announce Type: replace Abstract: Legal text generated by large language models (LLMs) can usually achieve reasonable factual accuracy, but it frequently fails to adhere to the speci

safetyarxiv-cs-cl

Does Playing it Safe Count as Faithfulness? Reassessing LVLM Hallucination Mitigation Methods

model-releasesarxiv-cs-cv

arXiv:2609.01888v1 Announce Type: new Abstract: Recent inference-time hallucination mitigation methods for large vision-language models (LVLMs) report strong gains on hallucination benchmarks. However

Evidence-Guided Detection, Localization and Explanation for Text-Centric Image Forensics

arXiv:2609.02097v1 Announce Type: new Abstract: The rapid progress of AIGC has made text-centric image manipulation increasingly accessible, creating new forensic challenges that require not only auth

local-aiarxiv-cs-cv

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2312.06315v2 Announce Type: replace Abstract: Warning: This paper contains content that may be offensive or upsetting. There has been a significant increase in the usage of large language models

HarmReduction: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs

model-releasesarxiv-cs-cl

arXiv:2507.21815v2 Announce Type: replace Abstract: Millions of individuals' well-being are challenged by the harms of substance use. Harm reduction as a public health strategy provides non-judgementa

Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives

arXiv:2609.01736v1 Announce Type: cross Abstract: Large language models (LLMs) augmented with external tools have demonstrated remarkable capability in solving complex real-world tasks. However, exist

Humanoid Safe Stop via Learned Stoppability Value

arXiv:2609.02358v1 Announce Type: cross Abstract: Humanoid robots responding to emergency stop commands typically execute a fixed maneuver, without reasoning about whether a safe stop is actually feas

safetyarxiv-cs-lg

Hybrid Retrieval-Augmented Generation with Knowledge Graph Expansion, RRF Fusion, and Per-Chunk Grounded Evaluation for Enterprise Document Search

arXiv:2609.01617v1 Announce Type: cross Abstract: Getting accurate, grounded answers out of large enterprise document repositories is a difficult problem. Dense vector retrieval alone frequently perfo

Improving Evaluation Realism with Inference-Time Compute and Deployment Scaffolds

arXiv:2609.02302v1 Announce Type: new Abstract: A core obstacle to alignment evaluation is evaluation awareness: capable models can tell when they are being tested rather than deployed, weakening the

Multimodal Language Models as Text-to-Image Model Evaluators

arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

Zeta-Lite: A Concurrent, Branchable In-Browser SQL Database for Agentic Memory

arXiv:2609.01818v1 Announce Type: cross Abstract: The browser has become a first-class database host: applications increasingly want to store, query, and reason over structured data entirely on the cl

Are We There Yet? Assessing Computer-Use Agents for Blind Users' Accessible Interaction with Desktop Applications

arXiv:2609.00524v1 Announce Type: cross Abstract: Computer-use agents are emerging as a paradigm for agentic human-AI interaction, combining language reasoning with multi-modal interface grounding to

Causal Probing for Internal Visual Representations in Multimodal Large Language Models

arXiv:2605.05593v2 Announce Type: replace Abstract: Despite the remarkable success of Multimodal Large Language Models (MLLMs) across diverse tasks, the internal mechanisms governing how they encode a

DSG: Dynamic 3D Scene Graph Construction for Embodied Agents in Changing Indoor Environments

model-releasesarxiv-cs-ro

arXiv:2609.00619v1 Announce Type: new Abstract: In indoor environments, object positions frequently change due to human activities or embodied-agent interactions, causing previously constructed scene

Dual Process Motion Planning

arXiv:2609.01260v1 Announce Type: new Abstract: Robotic systems are deeply embedded in both industry and everyday life, where they are expected to act with speed, precision, and reliability. Classical

DualStake: Dual-Path Confidence Calibration in Deep Research Agents

arXiv:2609.00935v1 Announce Type: cross Abstract: Deep Research agents tackle knowledge-intensive tasks through multi-round retrieval and decision-oriented generation. However, these agents suffer fro

EvoSCM: Scientific Belief Revision Through Causal Model Evolution and Experimentation

arXiv:2609.01526v1 Announce Type: new Abstract: Scientific agents must learn not only how to reason, but also what to believe. However, existing LLM agents typically express scientific hypotheses in f

Applications

Feed-Forward Multi-view Multi-person Reconstruction with Contrastive Human-Aware 3D Representation

arXiv:2609.00745v1 Announce Type: new Abstract: Multi-view human reconstruction has been extensively studied under simplified settings, yet robust and efficient multi-person reconstruction in unconstr

applicationsarxiv-cs-cv

GRRM: Group Relative Reward Modeling for Machine Translation

arXiv:2602.14028v2 Announce Type: replace Abstract: While Group Relative Policy Optimization (GRPO) offers a powerful framework for LLM post-training, its effectiveness in open-ended domains like Mach

safetyarxiv-cs-cl

Make Some Noise: Unsupervised Remote Sensing Change Detection Using Latent Space Perturbations

arXiv:2602.19881v2 Announce Type: replace-cross Abstract: Unsupervised remote sensing change detection (UCD) aims to localise changes between two images of the same region without relying on labelled

MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

arXiv:2603.03517v2 Announce Type: replace-cross Abstract: General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and perform

Probing Factual Knowledge Transfer with Training Data Interventions

arXiv:2609.01341v1 Announce Type: cross Abstract: Do multilingual language models transfer factual knowledge across languages during continued pretraining, or do they mostly recall facts learned direc

RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation

arXiv:2609.00918v1 Announce Type: new Abstract: Large language models are increasingly used as interactive recommender assistants. Their evaluation should therefore go beyond plausible item recommenda

SG-AMP: Scene-Graph-Guided Active Perception and Semantics-Aware Motion Planning for Pepper Plants

arXiv:2609.01579v1 Announce Type: new Abstract: We present SG-AMP, integrating robust depth completion with input-conditioned uncertainty, persistent panoptic mapping, plant scene-graph reasoning, and

researcharxiv-cs-ro

Slow to See, Slow to Suppress: Understanding the Effects of Modality in Context-Memory Conflicts

arXiv:2609.00293v1 Announce Type: new Abstract: We investigate how vision-language models (VLMs) handle context-memory conflicts; that is, situations in which the model is given information in context

safetyarxiv-cs-cl

SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generation

arXiv:2609.00427v1 Announce Type: new Abstract: The exponential growth of wireless devices is driving unprecedented spectrum demand, pushing spectrum management toward more fine-grained decisions acro

SupraTok: Cross-Boundary Tokenization for Enhanced Language Model Performance

arXiv:2508.11857v3 Announce Type: replace-cross Abstract: Tokenization remains a persistent bottleneck in language modeling, especially when vocabulary learning is limited by whitespace boundaries. We

Towards a Belief-Based World Model for LLM Agents

arXiv:2609.00455v1 Announce Type: new Abstract: Large language models (LLMs) are being used as policies for autonomous decision-making and planning in many domains. Despite their strong reasoning capa

Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness

arXiv:2609.00050v1 Announce Type: cross Abstract: Agentic AI is enabling cloud-based workflows in which autonomous agents reason over operational state, invoke authorized tools, modify software and in

Towards Generalizable Visually Grounded Exploration of Household Devices

arXiv:2609.00845v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) have demonstrated impressive capabilities in static visual recognition and high-level semantic reas

TRIAGE: Three-level Routing and Intelligent Agent Guidance for Efficient Execution

model-releasesarxiv-cs-lg

arXiv:2609.01428v1 Announce Type: new Abstract: Large Language Model (LLM) agents based on the ReAct paradigm have demonstrated remarkable capabilities in tool use and task execution. However, ReAct s

VerNav: Verifier-First Low-Latency Vision-and-Language Navigation

model-releasesarxiv-cs-cv

arXiv:2609.00920v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) requires an agent to navigate through unseen 3D environments according to natural-language instructions. Explicit

ViPlan: A Benchmark for Visual Planning with Symbolic Predicates and Vision-Language Models

arXiv:2505.13180v3 Announce Type: replace Abstract: Integrating Large Language Models with symbolic planners is a promising direction for obtaining verifiable and grounded plans, with recent works ext

Applications

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI

arXiv:2607.17883v2 Announce Type: replace-cross Abstract: Enterprises will not deploy AI agents they cannot trust, and the most-cited reason for distrust is hallucination: confident, fluent output tha

applicationsarxiv-cs-ai

Adversarial Trust Poisoning in Vehicular Collaborative Perception

arXiv:2605.22122v2 Announce Type: replace-cross Abstract: Collaborative perception (CP) enables connected and autonomous vehicles to share sensor data and jointly reason about their environment. To de

Analytic Dynamics: Learning Physics-Grounded Representation for Fast Intrinsic Dynamics Inference from Monocular Videos

model-releasesarxiv-cs-cv

arXiv:2608.31025v1 Announce Type: new Abstract: Inferring object dynamics from visual observations is essential for intelligent agents to reason about and interact with the physical world, yet remains

Answer Probing-Guided Search for Diverse Solution Exploration of LLMs

arXiv:2608.30345v1 Announce Type: new Abstract: Generating multiple diverse and high-quality solutions is valuable for many applications, such as code-test generation and drug discovery. However, Larg

Beyond the Answer Key: Robustness Evaluation of Large Language Models for Step-Level Mathematical Verification

arXiv:2608.28725v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as graders, verifiers, and process auditors, but most mathematical evaluations still emphasize final-

Candidate supply and answer selection shape the value of LLM judging in multi-agent systems

arXiv:2608.25937v2 Announce Type: replace Abstract: Multi-agent systems (MAS) sometimes already have the potential to answer correctly, but still report a wrong answer. Explaining this outcome is diff

COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2608.30109v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on extensive scientific research are increasingly integrated as assistants for scientific discovery. However, most

Hardware

Dancing Stick Figures: An Introductory Dataset for Training Video Generation Models

arXiv:2608.29123v1 Announce Type: new Abstract: Training a video-generation model from scratch is hard for reasons that precede model design. The feedback loop is long: a failure that appears only aft

hardwarearxiv-cs-cv

Defending Wearable VLMs Against Private Attribute Inference

arXiv:2608.28691v1 Announce Type: cross Abstract: Wearable VLM pipelines promise continuous multimodal assistance from egocentric visual capture: a user asks a task-driven question about the surroundi

Designing an Auditable LLM-Supported Workflow for Qualitative Thematic Analysis

arXiv:2608.30543v1 Announce Type: new Abstract: Large Language Models (LLMs) offer new possibilities for scaling qualitative analysis, but existing applications often provide limited methodological tr

Detect Before You Attribute: Cascade Failure Attribution for Multi-Agent Systems

arXiv:2608.29646v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong potential in solving complex tasks through multi-step reasoning, yet they remain vulnerable to