Search: “reasoning”

Geometric and Semantic Coupling for Interaction Understanding in 3D Scenes

arXiv:2609.25247v1 Announce Type: new Abstract: Interaction understanding in 3D scenes requires a joint description of movable parts, their motion, and the regions through which they can be operated.

researcharxiv-cs-cv

23 Sept 2026

Applications

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis

DGX agent

arXiv:2410.14948v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their train

applicationsarxiv-cs-cl

23 Sept 2026

PhysAI-Bench: A Benchmark for LLM-Based Agentic Decision-Making in Autonomous UAV-Centric Physical AI

arXiv:2609.23695v1 Announce Type: new Abstract: Recent advances in Physical AI have accelerated the use of foundation models in autonomous systems such as unmanned aerial vehicles (UAVs), which must p

23 Sept 2026

Tutorials

You've Seen Enough: Quality-Constrained Image Coding for Machines

arXiv:2609.25108v1 Announce Type: new Abstract: Visual data is increasingly consumed by machine-vision systems rather than by human observers. Image Coding for Machines (ICM) compresses images assumin

tutorialsarxiv-cs-cv

23 Sept 2026

ARM: Attention with Routed-Memory for Learnable Sparse Control

arXiv:2609.24417v1 Announce Type: new Abstract: Despite advances in long-context inference, large language models (LLMs) remain fundamentally limited by the key-value (KV) caching mechanisms that are

safetyarxiv-cs-lg

Ask Before It Tells: Benchmark-to-Robot Body-Cue Transfer for a Question-First Bedside Robot

model-releasesarxiv-cs-ro

arXiv:2609.24099v1 Announce Type: new Abstract: Body-cue recognition can support assistive robots, but benchmark accuracy does not guarantee reliable behavior under a robot-camera viewpoint. We presen

Compound-QA: A Benchmark for Evaluating LLMs on Compound Questions

arXiv:2411.10163v3 Announce Type: replace Abstract: Large language models (LLMs) demonstrate remarkable performance across various tasks, prompting researchers to develop diverse evaluation benchmarks

DeViGrasp: Robust Visual Mobile Grasping for Quadruped Manipulators under Degraded Perception

model-releasesarxiv-cs-ro

arXiv:2609.22278v1 Announce Type: new Abstract: Quadruped manipulators enable mobile grasping in complex environments, yet their whole-body control policies remain vulnerable to unreliable onboard vis

Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection

arXiv:2609.24359v1 Announce Type: new Abstract: Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while

local-aiarxiv-cs-cv

EmbodiedDiffusion: End-to-End Traversability-Guided Visual Diffusion for Heterogeneous Robot Navigation

arXiv:2512.02851v5 Announce Type: replace Abstract: Visual traversability estimation is central to autonomous navigation, yet most approaches either rely on prompt-driven Vision-Language Model (VLM) o

agentsarxiv-cs-ro

Applications

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

arXiv:2510.26915v2 Announce Type: replace Abstract: While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large langua

applicationsarxiv-cs-ro

LegendBench: A Diagnostic Benchmark for Legend Understanding with Counterfactual Interventions

arXiv:2609.24172v1 Announce Type: new Abstract: Legends are fundamental to chart understanding, as reliable interpretation requires correctly binding legend entries to corresponding visual marks. Whil

LLM-based Conversational AI Knowledge Assistant for MyBuddy Humanoid Robot

arXiv:2609.24742v1 Announce Type: new Abstract: Humanoid robots are increasingly being popular and developed for human-centered applications, yet their ability to provide intelligent conversations and

researcharxiv-cs-ro

Machine-Interpretable Information: Compiling Documents into Searchable and Readable Protocol States

arXiv:2609.23371v1 Announce Type: new Abstract: Long-context language models interface with external knowledge through raw natural language. In retrieval-augmented systems, this creates a persistent i

MinCU: A Fine-Grained Benchmark for Grounded Minimal-Change Understanding in Image Pairs

arXiv:2609.23336v1 Announce Type: new Abstract: Localizing and describing fine-grained differences between near-identical images is a critical yet underexplored capability for multimodal large languag

MSI-Bench: Evaluating Multi-Speaker Voice Interaction for Collaborative AI Agents

arXiv:2609.24812v1 Announce Type: new Abstract: Voice provides a natural and immediate interface for AI agents. Many settings in which voice agents could be useful, including meetings, households, and

Pay More Attention To Text In High-Resolution MLLMs

arXiv:2609.23495v1 Announce Type: new Abstract: Failures of high-resolution MLLMs are commonly attributed to a visual problem, motivating zooming, cropping, and related visual interventions to recover

researcharxiv-cs-cv

SCoP: Structured Constraint Parsing for Evidence-Space Control in Temporal Knowledge Graph Question Answering

arXiv:2609.22213v1 Announce Type: new Abstract: Temporal Knowledge Graph Question Answering (TKGQA) requires answer inference from evidence that is both structurally valid and temporally admissible. E

Seeing Through Conflicts: Improving Instruction Hierarchy Alignment in Vision-Language Models

arXiv:2609.22234v1 Announce Type: new Abstract: Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in te

safetyarxiv-cs-cl

STEVE: Stabilizing Textual Gradient-Based Prompt Optimization via Error-Driven Refinement and Regularized Verification

arXiv:2609.23716v1 Announce Type: new Abstract: Textual-gradient methods automate prompt optimization through natural-language feedback, but their iterative updates can be unstable. We identify two so

Token Utility Is Selection-Conditioned: Coupled Selection of Prompt Context and Response Supervision for Efficient Instruction Tuning

arXiv:2609.22943v1 Announce Type: new Abstract: Efficient large language model (LLM) instruction tuning requires selecting response supervision with supporting prompt context. Existing methods typical

researcharxiv-cs-lg

Toward Personalized Sleep Guidance from Wearable Data Using Language Models

arXiv:2609.22463v1 Announce Type: new Abstract: Sleep monitoring using wearable data has shown promise for personal health, yet large language model (LLM)-based summarization and question answering re

local-aiarxiv-cs-cl

XYEval: Agents say yes to bad advice

arXiv:2609.23939v1 Announce Type: new Abstract: Effective communication between users and AI agents is essential for human-AI collaboration. The XY problem is a well-known communication pitfall where

AgentVidBench: A Multi-Hop Video Question Answering Benchmark for Evaluating MLLM Agents

arXiv:2609.21386v1 Announce Type: cross Abstract: Comprehensive video understanding is crucial for advancing artificial intelligence toward the intricate dynamics of the physical world. While recent a

Attention-Aware Routing: Coupling Routing and Attention in MoEs

arXiv:2609.20974v1 Announce Type: new Abstract: In Mixture-of-Experts language models, the router typically selects and weights experts based on the token's hidden state, utilizing limited contextual

researcharxiv-cs-ai

BEAT-Net: Injecting Biomimetic Spatio-Temporal Priors for Interpretable ECG Diagnosis

arXiv:2601.07316v2 Announce Type: replace-cross Abstract: Automated electrocardiogram diagnosis using deep learning remains limited by signal-agnostic representations that treat multi-lead recordings

Elastic Threshold Attention: Learned Contextual Sparsity for Long-Context Decoding

arXiv:2609.20888v1 Announce Type: new Abstract: Massive KV caches can cause severe memory-bandwidth bottlenecks during long-context decoding. Sparse attention methods mitigate this via selective loadi

local-aiarxiv-cs-lg

GameASG-Bench: Benchmarking Autonomous Software Generation for Game Development

arXiv:2609.21293v1 Announce Type: new Abstract: Autonomous software generation (ASG) aims to turn human requirements into executable applications, but delivering these applications does not necessaril

Gradient-Stable Attention Heads Signal LLM Correctness

arXiv:2602.13699v2 Announce Type: replace Abstract: Large language models (LLMs) often generate plausible yet incorrect answers, posing risks in safety-critical settings such as medicine. Human evalua

safetyarxiv-cs-lg

MME-Safety: A Fine-grained Benchmark for Safety Evaluation of MLLMs

arXiv:2609.20850v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) show remarkable advancements, their cross-modal capabilities introduce complex vulnerabilities that easil

ProTracer: Proprioception-Guided Failure Diagnosis in Robot Manipulation

arXiv:2609.21369v1 Announce Type: cross Abstract: This paper presents a comprehensive framework for robot manipulation failure analysis that includes binary failure detection, failure categorization,

TrialAtlas: Multi-Agent Research Organization for Clinical Trial Design and Optimization

arXiv:2609.21859v1 Announce Type: new Abstract: Nearly 90% of drugs entering clinical development ultimately fail, despite billions of dollars in investment. Pharmaceutical companies therefore rely on

A Multi-Modal Generative Model for Tomato Disease Leaves Understanding

arXiv:2609.19555v1 Announce Type: cross Abstract: Artificial intelligence for plant disease analysis has advanced from task-specific classifiers to multi-modal models capable of jointly interpreting v

researcharxiv-cs-ai

A Neuropsychologically Grounded Evaluation of LLM Cognitive Abilities

arXiv:2603.02540v2 Announce Type: replace Abstract: Large language models (LLMs) display a unified 'general factor' of capability across 10 benchmarks (a finding confirmed by our factor analysis of 15

A Simulation Platform for AUV Fault Recovery: Exploring LLM-Based Diagnostic Strategies

arXiv:2609.20620v1 Announce Type: cross Abstract: Autonomous underwater vehicles (AUVs) operating beyond reliable communications must recover from failures without human intervention. We investigate a

local-aiarxiv-cs-ai

Chain-of-Thought Entropy as a Reliability Signal: A Preregistered Reproduction

arXiv:2609.19606v1 Announce Type: new Abstract: This empirical study is an independent reproduction of the dissociation Zhao reported in 2026. The shape of a large language model's chain-of-thought en

Large Language Model Agents for Evidence Based Genetic Disease Severity Classification

arXiv:2609.19569v1 Announce Type: cross Abstract: Disease severity classification for genetic conditions is subjective and labor-intensive, creating bottlenecks in genomic screening, where commercial

agentsarxiv-cs-ai

Neuro-Symbolic Agentic AI for Networked Low-Altitude UAVs

arXiv:2609.19961v1 Announce Type: new Abstract: Networked low-altitude unmanned aerial vehicles (UAVs) need reliable and adaptive decision-making capabilities to operate under uncertain observations,

agentsarxiv-cs-ai

NeuSOGA3D: A Neuro-Symbolic Framework for Explainable 3D Geometric Reconstruction

arXiv:2609.20323v1 Announce Type: new Abstract: Three-dimensional reconstruction from unorganized point clouds remains a challenging problem in computer vision, geometric modeling, and computer-aided

QEncodeBench: Can Large Language Models Encode Classical Problems into Verified Quantum Oracles?

arXiv:2609.20319v1 Announce Type: cross Abstract: Grover search, amplitude amplification, and quantum counting all rely on the same reusable subroutine, a phase oracle, whose construction the algorith

agentsarxiv-cs-lg

SIMLIFE: Pattern Understanding for Long-Horizon Human-Agent Partnership

arXiv:2609.19610v1 Announce Type: new Abstract: Understanding humans over long horizons requires agents to infer not only what people need in the moment, but also how routines form, why they repeat, a

What Does Privileged Information Add to On-Policy Self-Distillation?

arXiv:2609.20612v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) lets a language model learn from a frozen copy of itself that sees an answer or a worked solution. Giving the teacher

When AI Agents Commit: Cognitive Serializability Across Data, Evidence, Policy, and Authority

arXiv:2609.20261v1 Announce Type: new Abstract: Autonomous agents derive concrete mutations from database reads, retrieved evidence, policy, beliefs, and delegated authority. Those inputs may change w

safetyarxiv-cs-ai

AeroWeaver: An Embodied-Agent Harness for Weaving Aerial Skills into Distributed, Adaptive Swarm Execution

arXiv:2609.18520v1 Announce Type: new Abstract: Collective intelligence is a collaborative autonomy paradigm in which multiple agents pursue shared objectives through local perception, information exc

local-aiarxiv-cs-ai

Align, Integrate, and Fire: Efficient Token-Level Alignment for Zero-Shot SpeechLLMs

arXiv:2609.18516v1 Announce Type: new Abstract: While Large Language Models excel in natural language processing, efficiently extending their capabilities to spoken input remains a significant challen

Audio for Sports Highlight Detection: A Comparative Empirical Study

arXiv:2609.17923v1 Announce Type: new Abstract: Sports highlight detection aims to identify the most exciting and meaningful moments from long sports videos. While existing methods often emphasize vis

Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments

arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro

agentsarxiv-cs-ai

FairCompressAgent: An Agentic Framework for Fairness-Aware Model Compression for FPGA Deployment

arXiv:2609.17786v1 Announce Type: new Abstract: Fairness-aware model compression requires selecting methods and configurations that balance accuracy, fairness, and deployment cost. These decisions bec

safetyarxiv-cs-ai