Search: “research”

Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems

arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackling complex reasoning, planning, and tool-use tasks

safetyarxiv-cs-cl

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CLFEC: A New Task for Unified Linguistic and Factual Error Correction in paragraph-level Chinese Professional Writing

DGX agent

arXiv:2602.23845v2 Announce Type: replace Abstract: Chinese text correction has traditionally focused on spelling and grammar, while factual error correction is usually treated separately. However, in

model-releasesarxiv-cs-cl

5 Jun 2026

Coding with 'Enemy': Can Human Developers Detect AI Agent Sabotage?

arXiv:2606.05647v1 Announce Type: cross Abstract: AI coding agents are increasingly embedded in real-world software development, collaborating with human developers while gaining broader access to cod

CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments

arXiv:2606.06399v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models have shown growing promise, with their effectiveness resting on agents' ability to coordinate t

agentsarxiv-cs-cl

Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for Multimodal UI/UX Design Understanding

arXiv:2505.05026v5 Announce Type: replace Abstract: User interface (UI) design goes beyond visuals to shape user experience (UX), underscoring the shift toward UI/UX as a unified concept. While recent

Local Ai

GenTract: Generative Global Tractography

arXiv:2511.13183v2 Announce Type: replace Abstract: Tractography is the process of inferring the trajectories of white-matter pathways in the brain from diffusion magnetic resonance imaging (dMRI). Lo

local-aiarxiv-cs-cv

HOLO: Homography-Guided Pose Estimator Network for Fine-Grained Visual Localization on SD Maps

arXiv:2601.02730v3 Announce Type: replace Abstract: Visual localization on standard-definition (SD) maps has emerged as a promising low-cost and scalable solution for autonomous driving. However, exis

Improving Answer Extraction in Context-based Question Answering Systems Using LLMs

arXiv:2606.06197v1 Announce Type: new Abstract: Question answering (QA) systems have achieved notable progress with the advent of large language models (LLMs). However, they still face challenges in a

Applications

Learning Predictive Visuomotor Coordination

arXiv:2503.23300v2 Announce Type: replace Abstract: Understanding and predicting human visuomotor coordination is crucial for applications in robotics, human-computer interaction, and assistive techno

applicationsarxiv-cs-cv

Pitfalls of Evaluating Language Models with Open Benchmarks

arXiv:2507.00460v3 Announce Type: replace Abstract: Open Large Language Model (LLM) benchmarks, such as HELM and BIG-Bench, provide standardized and transparent evaluation protocols that support compa

safetyarxiv-cs-cl

Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning

arXiv:2606.05506v1 Announce Type: new Abstract: We propose a sensor-guided adaptive contrastive learning framework for visual representation learning in PointGoal navigation. During training, privileg

safetyarxiv-cs-cv

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation

arXiv:2606.05660v1 Announce Type: new Abstract: Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety t

TopoPult-SSL: Gland-Mask-Free Cross-Device Meibomian Gland Segmentation via Self-Distilled Weak Clinical Priors

arXiv:2606.05347v1 Announce Type: new Abstract: Every new clinical imaging device creates a domain shift where dense gland masks are expensive yet cheap clinical signals -- eyelid outlines, Pult grade

Towards a Data Flywheel for Embodied Intelligence in Logistics

arXiv:2606.05960v1 Announce Type: new Abstract: Embodied intelligence is moving from laboratory demonstrations toward industrial deployment, with the logistics industry serving as a key application sc

safetyarxiv-cs-ro

Unsupervised Skill Discovery for Agentic Data Analysis

arXiv:2606.06416v1 Announce Type: cross Abstract: Inference-time skill augmentation provides a lightweight way to improve data-analytic agents by injecting reusable procedural knowledge without updati

agentsarxiv-cs-cl

Using street view images and visual LLMs to predict heritage values for governance support: Risks, ethics, and policy implications

arXiv:2601.06056v2 Announce Type: replace-cross Abstract: During 2025 and 2026, the Energy Performance of Buildings Directive is being implemented in the European Union member states, requiring all me

safetyarxiv-cs-cv

Would you still call this Dax? Novel Visual References in VLMs and Humans

arXiv:2606.05409v1 Announce Type: cross Abstract: Vision-language models (VLMs), like human learners, are frequently exposed to new visual concepts, but how they map novel visual references to languag

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation

arXiv:2606.04172v1 Announce Type: new Abstract: Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dep

AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safety

arXiv:2606.04867v1 Announce Type: new Abstract: As AI companion platforms such as Replika and Character.AI rapidly grow, concerns about unsafe human-AI interactions have intensified. This study introd

An Open-Source Two-Stage Computer Vision Pipeline for Fine-Grained Vehicle Classification using Vision Transformers

arXiv:2606.05149v1 Announce Type: new Abstract: Vehicle body type is a significant determinant of cyclist injury severity in overtaking crashes, yet automated tools for classifying vehicles into injur

Analysis-Driven Procedural Generation of an Engine Sound Dataset with Embedded Control Annotations

model-releasesarxiv-cs-lg

arXiv:2603.07584v2 Announce Type: replace-cross Abstract: Computational engine sound modeling is central to the automotive audio industry, particularly for active sound design applications and virtual

Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?

arXiv:2606.04971v1 Announce Type: new Abstract: Machine learning engineering (MLE) agents promise to automate end-to-end ML pipeline development from raw data and natural language instructions, potent

safetyarxiv-cs-lg

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation

arXiv:2510.13272v3 Announce Type: replace Abstract: Inspired by the success of reinforcement learning (RL) in Large Language Model (LLM) training for domains like math and code, recent work has begun

agentsarxiv-cs-cl

Beyond Objective Equivalence: Constraint Injection for LLM-Based Optimization Modeling on Vehicle Routing Problems

arXiv:2606.04816v1 Announce Type: new Abstract: Large language models (LLMs) increasingly translate natural-language optimization problems into executable solver code. Yet for constraint-dense operati

CADET: A Modular Platform for Evaluating Distributed Cooperative Autonomy in Connected Autonomous Vehicles

model-releasesarxiv-cs-lg

arXiv:2606.04072v1 Announce Type: cross Abstract: Deep learning models are increasingly central to autonomous vehicle (AV) pipelines, yet their integration has traditionally followed a monolithic desi

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

arXiv:2606.04023v1 Announce Type: cross Abstract: While large language models (LLMs) have been extensively evaluated on code generation tasks for general-purpose programming and GPU-accelerated enviro

DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning

arXiv:2509.10247v1 Announce Type: cross Abstract: This letter introduces DiffAero, a lightweight, GPU-accelerated, and fully differentiable simulation framework designed for efficient quadrotor contro

safetyarxiv-cs-ai

Dynamic Multi-Pair Trading Strategy in Cryptocurrency Markets with Deep Reinforcement Learning

arXiv:2606.04574v1 Announce Type: new Abstract: This study aims to determine whether the application of Deep Reinforcement Learning (DRL) as a specialized execution overlay can enhance pair trading in

safetyarxiv-cs-lg

FinTradeBench: A Financial Reasoning Benchmark for LLMs

arXiv:2603.19225v3 Announce Type: replace-cross Abstract: Real-world financial decision-making is a challenging problem that requires reasoning over heterogeneous signals, including company fundamenta

Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment

arXiv:2606.04750v1 Announce Type: new Abstract: Instilling virtuous behavior in artificial intelligence has seen increasing interest. One of the techniques proposed is known as affinity-based reinforc

safetyarxiv-cs-ai

Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach

arXiv:2603.24747v2 Announce Type: replace Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for formal verification of agent protocols.

safetyarxiv-cs-ai

From Prompt to Process: a Process Taxonomy and Comparative Assessment of Frameworks Supporting AI Software Development Agents

arXiv:2606.04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles,

agentsarxiv-cs-ai

M^3Eval: Multi-Modal Memory Evaluation through Cognitively-Grounded Video Tasks

arXiv:2606.05008v1 Announce Type: cross Abstract: As multi-modal models advance towards long-form video understanding, memory emerges as a critical capability. Despite substantial efforts in developin

Tutorials

Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models

arXiv:2606.04326v1 Announce Type: cross Abstract: Concept bottleneck models predict outcomes from high-level concepts detected in inputs. Although concepts provide a simple way to reap benefits from i

tutorialsarxiv-cs-ai

Tutorials

Modeling and Interpreting Teamwork Dynamics in Cancer Care Outcome Prediction

arXiv:2606.04499v1 Announce Type: cross Abstract: Cancer care requires a longitudinal approach in which treatments are planned and delivered over time according to the needs of each individual patient

tutorialsarxiv-cs-lg

Recent Advances and Trends in Learning-based 3D Representations

arXiv:2606.04871v1 Announce Type: new Abstract: The selection of an appropriate 3D representation is a fundamental design decision that dictates the efficiency, quality, and capabilities of modern com

agentsarxiv-cs-cv

Scene-Centric Unsupervised Video Panoptic Segmentation

arXiv:2606.04925v1 Announce Type: new Abstract: Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regio

SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models

arXiv:2606.04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coor

The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?

arXiv:2606.04455v1 Announce Type: new Abstract: Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next

Applications

Towards Evaluating the Robustness of Visual State Space Models

arXiv:2406.09407v3 Announce Type: replace Abstract: Vision State Space Models (VSSMs), a novel architecture that combines the strengths of recurrent neural networks and latent variable models, have de

applicationsarxiv-cs-cv

Tree-Based Formalization of Multi-Agent Complementarity in Human-AI Interactions

arXiv:2606.04779v1 Announce Type: new Abstract: Complementarity is the case in which a human--AI interaction (HAI) outperforms the best prediction benchmark available among its members. Although this

Tutorials

A Systematic Evaluation of Current Architectures in Wind Power Forecasting

arXiv:2606.02849v1 Announce Type: new Abstract: Interval wind speed forecasting is essential for the efficient integration of wind energy into power systems, as it accounts for the inherent uncertaint

tutorialsarxiv-cs-lg

Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward

arXiv:2602.12430v4 Announce Type: replace-cross Abstract: The transition from monolithic language models to modular, skill-equipped agents marks a defining shift in how large language models (LLMs) ar

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics

arXiv:2507.21638v2 Announce Type: replace Abstract: The development of reinforcement learning (RL) algorithms has been largely driven by ambitious challenge tasks and benchmarks. Games have dominated

Applications

Attend to Anything: Foundation Model for Unified Human Attention Modeling

arXiv:2606.03540v1 Announce Type: new Abstract: Existing human attention (saliency) modeling methods persist as highly fragmented across modalities, scenes, and task formulations. Consequently, even w

applicationsarxiv-cs-cv

AVTrack: Audio-Visual Tracking in Human-centric Complex Scenes

arXiv:2606.02724v1 Announce Type: cross Abstract: Audio-visual speaker tracking aims to localize and track active speakers by leveraging auditory and visual cues, enabling fine-grained, human-centric

BEV-ODOM2: Enhanced BEV-based Monocular Visual Odometry with PV-BEV Fusion and Dense Flow Supervision for Ground Robots

arXiv:2509.14636v2 Announce Type: replace Abstract: Scale-consistent ego-motion estimation is fundamental for autonomous ground robots. Bird's-Eye-View (BEV) representation naturally addresses the sca

CANMOT: Class-Aware Noise Modeling for Multi-Object Tracking in Autonomous Driving

arXiv:2606.03590v1 Announce Type: new Abstract: Kalman filter (KF)-based multi-object tracking (MOT) remains a strong baseline for autonomous driving due to its strong performance, computational effic