Search: “agents”

arXiv:2510.01857v3 Announce Type: replace Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces o

local-aiarxiv-cs-ai

24 Apr 2026

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Safety

Task-specific Subnetwork Discovery in Reinforcement Learning for Autonomous Underwater Navigation

DGX agent

arXiv:2604.21640v1 Announce Type: cross Abstract: Autonomous underwater vehicles are required to perform multiple tasks adaptively and in an explainable manner under dynamic, uncertain conditions and

safetyarxiv-cs-ai

24 Apr 2026

SweRank: Software Issue Localization with Code Ranking

arXiv:2505.07849v2 Announce Type: replace-cross Abstract: Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language

23 Apr 2026

Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling

arXiv:2510.08145v2 Announce Type: replace Abstract: Large Language Models (LLMs) as automatic evaluators, commonly referred to as LLM-as-a-Judge, have also attracted growing attention. This approach p

22 Apr 2026

Decoding AI Tutor Effects for Educational Measurement: Temporal, Multi-Outcome, and Behavior-Cognitive Analysis

arXiv:2604.16366v1 Announce Type: cross Abstract: Artificial intelligence (AI) tutors have become increasingly popular in learning environments. In this study, we propose an AI agent prototype framewo

Heterogeneous Self-Play for Realistic Highway Traffic Simulation

arXiv:2604.16406v1 Announce Type: cross Abstract: Realistic highway simulation is critical for scalable safety evaluation of autonomous vehicles, particularly for interactions that are too rare to stu

LookasideVLN: Direction-Aware Aerial Vision-and-Language Navigation

arXiv:2604.17190v1 Announce Type: new Abstract: Aerial Vision-and-Language Navigation (Aerial VLN) enables unmanned aerial vehicles (UAVs) to follow natural language instructions and navigate complex

agentsarxiv-cs-cv

MoCo: A One-Stop Shop for Model Collaboration Research

arXiv:2601.21257v2 Announce Type: replace Abstract: Advancing beyond single monolithic language models (LMs), recent research increasingly recognizes the importance of model collaboration, where multi

OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

arXiv:2604.18486v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature

agentsarxiv-cs-cl

Research

Tool Learning Needs Nothing More Than a Free 8B Language Model

arXiv:2604.17739v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a prevalent paradigm for training tool calling agents, which typically requires online interactive environments

researcharxiv-cs-cl

Aerial Multi-Functional RIS in Fluid Antennas-Aided Full-Duplex Networks: A Self-Optimized Hybrid Deep Reinforcement Learning Approach

arXiv:2604.14309v2 Announce Type: replace-cross Abstract: To address high data traffic demands of sixth-generation (6G) networks, this paper proposes a novel architecture that integrates autonomous ae

safetyarxiv-cs-ai

20 Apr 2026

NLP needs Diversity outside of 'Diversity'

arXiv:2604.14595v1 Announce Type: new Abstract: This position paper argues that recent progress with diversity in NLP is disproportionately concentrated on a small number of areas surrounding fairness

17 Apr 2026

TableNet A Large-Scale Table Dataset with LLM-Powered Autonomous

arXiv:2604.13041v1 Announce Type: cross Abstract: Table Structure Recognition (TSR) requires the logical reasoning ability of large language models (LLMs) to handle complex table layouts, but current

17 Apr 2026

Tutorials

World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems

arXiv:2604.14732v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for building embodied agents that ground perception and language into action.

tutorialsarxiv-cs-lg

17 Apr 2026

Beyond State Consistency: Behavior Consistency in Text-Based World Models

arXiv:2604.13824v1 Announce Type: new Abstract: World models have been emerging as critical components for assessing the consequences of actions generated by interactive agents in online planning and

C^2T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination

arXiv:2604.13098v1 Announce Type: cross Abstract: State-of-the-art (SOTA) urban traffic control increasingly employs Multi-Agent Reinforcement Learning (MARL) to coordinate Traffic Light Controllers (

safetyarxiv-cs-cv

Red Skills or Blue Skills? A Dive Into Skills Published on ClawHub

model-releasesarxiv-cs-cl

arXiv:2604.13064v1 Announce Type: new Abstract: Skill ecosystems have emerged as an increasingly important layer in Large Language Model (LLM) agent systems, enabling reusable task packaging, public d

Training-Free Test-Time Contrastive Learning for Large Language Models

arXiv:2604.13552v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong reasoning capabilities, but their performance often degrades under distribution shift. Existing test-tim

agentsarxiv-cs-cl

A Comparison of Reinforcement Learning and Optimal Control Methods for Path Planning

arXiv:2604.12628v1 Announce Type: cross Abstract: Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge. While traditional optimal control methods can find idea

safetyarxiv-cs-ro

BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities

arXiv:2603.27552v2 Announce Type: replace Abstract: Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed acr

agentsarxiv-cs-lg

CompliBench: Benchmarking LLM Judges for Compliance Violation Detection in Dialogue Systems

model-releasesarxiv-cs-cl

arXiv:2604.12312v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as task-oriented agents in enterprise environments, ensuring their strict adherence to complex

Incentivizing High-Quality Human Annotations with Golden Questions

arXiv:2505.19134v2 Announce Type: replace-cross Abstract: Human-annotated data plays a vital role in training large language models (LLMs), such as supervised fine-tuning and human preference alignmen

Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids

arXiv:2604.11909v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems requires solar forecasting algorithms that respect atmospheric thermodynamics. Contem

A Survey on Deep Learning Techniques for Action Anticipation

arXiv:2309.17257v2 Announce Type: replace Abstract: The ability to anticipate possible future human actions is essential for a wide range of applications, including autonomous driving and human-robot

agentsarxiv-cs-cv

ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing

arXiv:2604.11103v1 Announce Type: cross Abstract: Role-playing has garnered rising attention as it provides a strong foundation for human-machine interaction and facilitates sociological research. How

Hardware

Characterizing Performance-Energy Trade-offs of Large Language Models in Multi-Request Workflows

arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,

hardwarearxiv-cs-ai

CheeseBench: Evaluating Large Language Models on Rodent Behavioral Neuroscience Paradigms

arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze

Energy-Efficient Federated Edge Learning For Small-Scale Datasets in Large IoT Networks

arXiv:2604.10662v1 Announce Type: new Abstract: Large-scale Internet of Things (IoT) networks enable intelligent services such as smart cities and autonomous driving, but often face resource constrain

agentsarxiv-cs-lg

GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs

arXiv:2511.11653v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have emerged as powerful tools for passage reranking in information retrieval, leveraging their superior reasonin

If an LLM Were a Character, Would It Know Its Own Story? Evaluating Lifelong Learning in LLMs

arXiv:2503.23514v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can carry out human-like dialogue, but unlike humans, they are stateless due to the superposition property. Howev

Local Ai

MeloTune: On-Device Arousal Learning and Peer-to-Peer Mood Coupling for Proactive Music Curation

arXiv:2604.10815v1 Announce Type: cross Abstract: MeloTune is an iPhone-deployed music agent that instantiates the Mesh Memory Protocol (MMP) and Symbolic-Vector Attention Fusion (SVAF) as a productio

local-aiarxiv-cs-ai

Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems

arXiv:2604.09963v1 Announce Type: cross Abstract: Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies

safetyarxiv-cs-ai

Shuffling the Data, Stretching the Step-size: Sharper Bias in constant step-size SGD

arXiv:2604.10373v1 Announce Type: cross Abstract: From adversarial robustness to multi-agent learning, many machine learning tasks can be cast as finite-sum min-max optimization or, more generally, as

Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning

arXiv:2602.21484v2 Announce Type: replace Abstract: 3D object detection is essential for autonomous driving and robotic perception, yet its reliance on large-scale manually annotated data limits scala

agentsarxiv-cs-cv

Utilizing and Calibrating Hindsight Process Rewards via Reinforcement with Mutual Information Self-Evaluation

arXiv:2604.11611v1 Announce Type: new Abstract: To overcome the sparse reward challenge in reinforcement learning (RL) for agents based on large language models (LLMs), we propose Mutual Information S

Hardware

CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference

arXiv:2604.08584v1 Announce Type: cross Abstract: Long-context LLMs increasingly rely on extended, reusable prefill prompts for agents and domain Q&A, pushing attention and KV-cache to become the domi

hardwarearxiv-cs-ai

Decentralized Opinion-Integrated Decision making at Unsignalized Intersections via Signed Networks

arXiv:2604.09351v1 Announce Type: cross Abstract: In this letter, we consider the problem of decentralized decision making among connected autonomous vehicles at unsignalized intersections, where exis

Koopman Operator Framework for Modeling and Control of Off-Road Vehicle on Deformable Terrain

arXiv:2603.28965v2 Announce Type: replace-cross Abstract: This work presents a hybrid physics-informed and data-driven modeling framework for predictive control of autonomous off-road vehicles operati

Yes, But Not Always. Generative AI Needs Nuanced Opt-in

arXiv:2604.09413v1 Announce Type: cross Abstract: This paper argues that a one-size-fits-all approach to specifying consent for the use of creative works in generative AI is insufficient. Real-world o

Assessing the Added Value of Onboard Earth Observation Processing with the IRIDE HEO Service Segment

arXiv:2604.07120v1 Announce Type: cross Abstract: Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Informatio

Formally Guaranteed Control Adaptation for ODD-Resilient Autonomous Systems

arXiv:2604.07414v1 Announce Type: cross Abstract: Ensuring reliable performance in situations outside the Operational Design Domain (ODD) remains a primary challenge in devising resilient autonomous s

HyperMem: Hypergraph Memory for Long-Term Conversations

model-releasesarxiv-cs-cl

arXiv:2604.08256v1 Announce Type: new Abstract: Long-term memory is essential for conversational agents to maintain coherence, track persistent tasks, and provide personalized interactions across exte

Semantic-Aware UAV Command and Control for Efficient IoT Data Collection

arXiv:2604.08153v1 Announce Type: new Abstract: Unmanned Aerial Vehicles (UAVs) have emerged as a key enabler technology for data collection from Internet of Things (IoT) devices. However, effective d

safetyarxiv-cs-ro

The End of the Foundation Model Era: Open-Weight Models, Sovereign AI, and Inference as Infrastructure

arXiv:2604.06217v1 Announce Type: cross Abstract: The foundation model era -- roughly 2020 to 2025 -- is over. The forces that defined it have inverted. Open source models have reached frontier perfor

safetyarxiv-cs-ai

AMR-Pose: An Active LED Marker-Based Relative Pose Estimation Framework With Probabilistic Switching PnP for Cooperative AUVs

arXiv:2608.12866v1 Announce Type: new Abstract: Reliable relative pose estimation between autonomous underwater vehicles (AUVs) is critical for cooperative ocean exploration, sampling, and multi-robot

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

Entropy-Augmented Multi-Objective Policy Optimization in Multiagent Systems

arXiv:2608.12534v1 Announce Type: cross Abstract: Autonomous agent teams deployed in settings such as marine and extraterrestrial outposts must coordinate actions to achieve optimal outcomes across mu

safetyarxiv-cs-ro

FUSE: Active Functional Affordance Grounding through Adaptive Semantic-Geometric Evidence Acquisition

model-releasesarxiv-cs-cv

arXiv:2608.12683v1 Announce Type: cross Abstract: Embodied agents must often identify and interact with objects based on their function rather than their identity, requiring them to actively acquire o