Search: “reasoning”

Toward Reducing Unproductive Container Moves: Predicting Service Requirements and Dwell Times

arXiv:2604.06251v1 Announce Type: new Abstract: This article presents the results of a data science study conducted at a container terminal, aimed at reducing unproductive container moves through the

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Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval

DGX agent

arXiv:2512.08410v2 Announce Type: replace Abstract: Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose

model-releasesarxiv-cs-cv

10 Apr 2026

Transforming the Voice of the Customer: Large Language Models for Identifying Customer Needs

arXiv:2503.01870v2 Announce Type: replace Abstract: Identifying customer needs (CNs) is fundamental to product innovation and marketing strategy. Yet for over thirty years, Voice-of-the-Customer (VOC)

tutorialsarxiv-cs-cl

TurboAgent: An LLM-Driven Autonomous Multi-Agent Framework for Turbomachinery Aerodynamic Design

arXiv:2604.06747v2 Announce Type: new Abstract: The aerodynamic design of turbomachinery is a complex and tightly coupled multi-stage process involving geometry generation, performance prediction, opt

Understanding Task Transfer in Vision-Language Models

arXiv:2511.18787v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) perform well on multimodal benchmarks but lag behind humans and specialized models on visual perception tasks like dep

tutorialsarxiv-cs-cv

Uni-ViGU: Towards Unified Video Generation and Understanding via A Diffusion-Based Video Generator

arXiv:2604.08121v1 Announce Type: new Abstract: Unified multimodal models integrating visual understanding and generation face a fundamental challenge: visual generation incurs substantially higher co

researcharxiv-cs-cv

Vision-Language Navigation for Aerial Robots: Towards the Era of Large Language Models

model-releasesarxiv-cs-ro

arXiv:2604.07705v1 Announce Type: new Abstract: Aerial vision-and-language navigation (Aerial VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and autonom

Visually-grounded Humanoid Agents

arXiv:2604.08509v1 Announce Type: new Abstract: Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively

Weighted Bayesian Conformal Prediction

model-releasesarxiv-cs-lg

arXiv:2604.06464v1 Announce Type: new Abstract: Conformal prediction provides distribution-free prediction intervals with finite-sample coverage guarantees, and recent work by Snell & Griffiths refra

XR-CareerAssist: An Immersive Platform for Personalised Career Guidance Leveraging Extended Reality and Multimodal AI

arXiv:2604.06901v1 Announce Type: cross Abstract: Conventional career guidance platforms rely on static, text-driven interfaces that struggle to engage users or deliver personalised, evidence-based in

3DCodeVerse: Exploring 3D Worlds as Code

arXiv:2610.22341v1 Announce Type: cross Abstract: We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises

A Responsibility-Centered Coordination Mechanism for Decentralized Multi-Agent Systems

arXiv:2610.21243v1 Announce Type: cross Abstract: Centralized orchestration provides comprehensive multi-agent coordination but creates bottlenecks in scalability, adaptability, and collective perform

Active Visual Perception: Opportunities and Challenges

arXiv:2512.03687v2 Announce Type: replace Abstract: Active visual perception enables an intelligent system to improve perception by controlling how visual evidence is acquired. However, differences in

tutorialsarxiv-cs-cv

AI Knows Where You Are: Exposure, Bias, and Inference in Multimodal Geolocation with KoreaGEO

arXiv:2506.03371v2 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have enabled accurate image-based geolocation, raising serious concerns about location privacy risk

All-in-One Memory: Process-Rewarded Reinforcement Learning for Memory Agents

arXiv:2610.21147v1 Announce Type: new Abstract: Large language models increasingly rely on external memory to answer queries grounded in long-horizon histories such as multi-session dialogues and leng

APRiL: An Open-ended Benchmark for Chinese Social Awareness in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.20785v1 Announce Type: new Abstract: Large language models are increasingly used in social interactions, where appropriate responses require recognizing implicit cues, inferring mental stat

Athanor: An Agent-Native System for Autonomous Post-Training Research

arXiv:2610.21055v1 Announce Type: new Abstract: Recursive self-improvement, in which AI systems build stronger AI systems, is one promising route to superintelligence. We study a weaker form that can

AVALON: Zero-Shot Indoor Navigation with Human-Seeded Topological Memory

arXiv:2610.21586v1 Announce Type: cross Abstract: Indoor service robots often enter unmapped buildings whose layouts and task constraints are already familiar to users. We address this human-familiar,

CriticaLLM: Using LLMs as Autonomous Game Master for Tabletop Role-Playing Games

arXiv:2610.21525v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive capabilities across many tasks, including processing large amounts of text, following instructions, a

Decomposing Brain-LLM Alignment with Interpretable Semantic Representations

arXiv:2610.21508v1 Announce Type: new Abstract: Large language models (LLMs) predict neural responses during naturalistic language comprehension, but the linguistic information underlying this brain a

Applications

Documenting Trofinetide Treatment Phenotypes in Rett Syndrome with a Dual-LLM Consensus Pipeline

arXiv:2610.22062v1 Announce Type: cross Abstract: Objective: Trofinetide, approved in 2023 as the first Rett syndrome treatment, lacks scalable real-world monitoring because chart review is labor-inte

applicationsarxiv-cs-cl

Evaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?

arXiv:2610.22333v1 Announce Type: new Abstract: Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiou

Local Ai

FedSkillGit: Federated Skill Evolution via Version Control

arXiv:2610.21348v1 Announce Type: new Abstract: Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience. In real-world deploym

local-aiarxiv-cs-ai

Fractional Power-of-Two Quantization for Efficient and Effective Multiplier-Free LLM Inference

arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene

From Observation to Intervention: Distilling Self-Generated In-Context Demonstrations via Executable Causal Intervention

arXiv:2610.21149v1 Announce Type: new Abstract: Self-generated In-Context Learning (ICL) enables LLMs to synthesize their own few-shot demonstrations, often outperforming manual prompts. However, exis

researcharxiv-cs-cl

From Research Goals to Scientific Closure: Evaluating Agents Through Evidence-Supported Physics Research

arXiv:2610.21767v1 Announce Type: new Abstract: Can AI agents organize scientific investigations that lead to well-supported conclusions? To evaluate this capability, we introduce PhysClosureBench, a

Full-Duplex Interaction with Speech, Expressions and Gestures

arXiv:2610.21452v1 Announce Type: cross Abstract: Human face-to-face conversation requires coordinating speech, gestures and expressions across both speaking and listening. We present ELLSA 2, an end-

tutorialsarxiv-cs-ai

Functional Subnetwork Localization for Efficient Continual Learning in Large Language Models

arXiv:2610.21537v1 Announce Type: new Abstract: Biological intelligence continually adapts to new information while retaining prior skills through localized plasticity. In contrast, continual learning

Gibbs-Gap Policy Optimization for Off-Policy RL with Verifiable Rewards

model-releasesarxiv-cs-cl

arXiv:2610.20814v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards often trains language models on responses generated by a different, possibly stale behavior policy. Cor

GRADS: Graph-Regulated Agentic Data Synthesis with Controllable Difficulty

arXiv:2610.21167v1 Announce Type: new Abstract: Deep research agents are increasingly deployed to retrieve precise information from large corpora, yet multi-hop, long-horizon tasks remain challenging.

Grounding Generative Verification in 3D Content

arXiv:2610.22360v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) and 3D generation have expanded 3D understanding and synthesis. However, beyond visual fidel

Human Interventions as Labels: Localizing, Steering, and (Sometimes) Editing the Computations Behind LLM Agent Failures

arXiv:2610.21708v1 Announce Type: cross Abstract: When an LLM agent misbehaves, a human steps in, and that intervention is usually discarded or replayed as training data. We treat it instead as a meas

Applications

IDfRA: Self-Verification for Iterative Design in Robotic Assembly

arXiv:2509.16998v2 Announce Type: replace Abstract: Design for Robotic Assembly (DfRA) remains largely dependent on manual planning and heuristic simulation, limiting scalability and robustness in com

applicationsarxiv-cs-ro

KULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Context

arXiv:2412.07251v1 Announce Type: cross Abstract: Large language models have exhibited significant enhancements in performance across various tasks. However, the complexity of their evaluation increas

Language Is a Security Surface for Agent Guards

arXiv:2610.22244v1 Announce Type: cross Abstract: Step-level guards decide, before each tool call, whether an agent's next action is safe given the user's request and the trajectory so far. Users writ

Language Models Share a Readout Bottleneck in Working Memory

arXiv:2610.21176v1 Announce Type: cross Abstract: Large language models (LLMs) reproduce a human working-memory signature on the N-back task: performance declines as memory load N increases, and error

Large Language Models Naively Recover Ethnicity from Individual Records

model-releasesarxiv-cs-cl

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

LEV: Thinking Fast and Deep with Looped Decision Models

arXiv:2610.20951v1 Announce Type: new Abstract: Decision models answer typed questions about an input with one probability per option, computed in a single forward pass without generating text. Like t

MedPAO-VL: Interpretable and Protocol-Compliant Agent for Structured Radiology Report Generation

arXiv:2610.21794v1 Announce Type: new Abstract: Despite the remarkable generalization capabilities of Large Language Models, generating clinically accurate and structured radiology reports from medica

safetyarxiv-cs-cv

MMSearch-OPD: Easy Made Hard, Hard Made Learnable for Long-Horizon Multimodal Search Agents

arXiv:2610.22240v1 Announce Type: new Abstract: Multimodal deep search is moving from short queries to long-horizon investigations that continually acquire evidence. However, training such agents rema

safetyarxiv-cs-cv

Momentum, Commentary Tone, and Earnings Surprise in LLM Financial Forecasts

arXiv:2610.22043v1 Announce Type: cross Abstract: Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, no

MSP: Modality Self-Play for Training Multimodal LLMs Without Paired Cross-Modal Data

arXiv:2610.20965v1 Announce Type: new Abstract: Large multimodal models have achieved remarkable progress by scaling model capacity and training on massive paired multimodal data. However, this paradi

NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness

arXiv:2609.08183v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) requires a concrete mechanism through which an AI system observes its capabilities and converts that evidence into

safetyarxiv-cs-cl

OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling

arXiv:2610.22355v1 Announce Type: new Abstract: Generative visual verifiers play a crucial role in advancing multimodal intelligence. To enhance the robustness of visual verifiers in complex multimoda

safetyarxiv-cs-cl

OpenGCUA: Toward a Fully Open Stack for Generalist Computer Use

arXiv:2610.22200v1 Announce Type: new Abstract: Computer use has reached a turning point: the focus is expanding from GUI-only interaction to systems that complete tasks on users' computers through vi

PremiseCheck: Efficient Fact-Checking of Human and AI Peer Reviews

arXiv:2610.21046v1 Announce Type: cross Abstract: Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate what a paper says. We introduce R

PriorityFEC: Deadline-Aware Streaming FEC for KV-Cache Handoff in Edge Multi-Agent Systems

arXiv:2610.21390v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are increasingly deployed at the edge to support complex tasks that require collaboration and informati

Prism-1: Position- and Rival-Independent Scoring for System One Models

arXiv:2610.22066v1 Announce Type: new Abstract: Given a state and a set of options, such as intents, tools or interface elements, System One decision models return a distribution over the options in o