Search: “agents”

GeoVision-Enabled Digital Twin for Hybrid Autonomous-Teleoperated Medical Responses

arXiv:2604.13248v1 Announce Type: new Abstract: Remote medical response systems are increasingly being deployed to support emergency care in disaster-affected and infrastructure-limited environments.

16 Apr 2026

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Safety

HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy

DGX agent

arXiv:2510.00695v3 Announce Type: replace-cross Abstract: Inherently, robotic manipulation tasks are history-dependent: leveraging past context could be beneficial. However, most existing Vision-Langu

safetyarxiv-cs-cv

16 Apr 2026

Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain

arXiv:2604.14013v1 Announce Type: cross Abstract: We promote in this paper the processing of radar data in the frequency domain to achieve higher robustness against noise and structural errors, especi

16 Apr 2026

Wireless bioelectronic control architectures for biohybrid robotic systems

arXiv:2603.24959v2 Announce Type: replace Abstract: Wireless bioelectronic interfaces are increasingly used to control tissue-engineered biohybrid robotic systems. However, a unifying engineering fram

16 Apr 2026

ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

model-releasesarxiv-cs-cl

arXiv:2602.11236v2 Announce Type: replace-cross Abstract: Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, man

Beyond Factual Grounding: The Case for Opinion-Aware Retrieval-Augmented Generation

arXiv:2604.12138v1 Announce Type: new Abstract: RAG systems have transformed how LLMs access external knowledge, but we find that current implementations exhibit a bias toward factual, objective conte

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch

model-releasesarxiv-cs-lg

arXiv:2603.24647v4 Announce Type: replace Abstract: The autoresearch repository enables an LLM agent to optimize hyperparameters by editing training code directly. We use it as a testbed to compare cl

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

safetyarxiv-cs-cl

Radar-Camera BEV Multi-Task Learning with Cross-Task Attention Bridge for Joint 3D Detection and Segmentation

arXiv:2604.12918v1 Announce Type: new Abstract: Bird's-eye-view (BEV) representations are the dominant paradigm for 3D perception in autonomous driving, providing a unified spatial canvas where detect

Research

Representing expertise accelerates learning from pedagogical interaction data

arXiv:2604.12195v1 Announce Type: new Abstract: Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals

researcharxiv-cs-cl

AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports

arXiv:2503.20654v4 Announce Type: replace-cross Abstract: Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existin

Autonomous Diffractometry Enabled by Visual Reinforcement Learning

arXiv:2604.11773v1 Announce Type: cross Abstract: Automation underpins progress across scientific and industrial disciplines. Yet, automating tasks requiring interpretation of abstract visual informat

safetyarxiv-cs-cv

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving

arXiv:2604.10856v1 Announce Type: cross Abstract: Open-loop (OL) to closed-loop (CL) gap (OL-CL gap) exists when OL-pretrained policies scoring high in OL evaluations fail to transfer effectively in c

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

arXiv:2509.00891v3 Announce Type: replace Abstract: Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse

Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration

arXiv:2601.07224v2 Announce Type: replace Abstract: While Hybrid Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) has become the standard paradigm for training LLM agents, effectiv

CSPO: Alleviating Reward Ambiguity for Structured Table-to-LaTeX Generation

arXiv:2604.10918v1 Announce Type: new Abstract: Tables contain rich structured information, yet when stored as images their contents remain 'locked' within pixels. Converting table images into LaTeX c

EDFNet: Early Fusion of Edge and Depth for Thin-Obstacle Segmentation in UAV Navigation

arXiv:2604.09694v1 Announce Type: new Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) must reliably detect thin obstacles such as wires, poles, and branches to navigate safely in real-world envir

General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging

arXiv:2604.09609v1 Announce Type: new Abstract: Human behavior models are essential as behavior references and for simulating human agents in virtual safety assessment of automated vehicles (AVs), yet

Hodoscope: Unsupervised Monitoring for AI Misbehaviors

arXiv:2604.11072v1 Announce Type: new Abstract: Existing approaches to monitoring AI agents rely on supervised evaluation: human-written rules or LLM-based judges that check for known failure modes. H

Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving

arXiv:2604.11549v1 Announce Type: cross Abstract: In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding

agentsarxiv-cs-lg

LLMs for Text-Based Exploration and Navigation Under Partial Observability

arXiv:2604.09604v1 Announce Type: new Abstract: Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language m

MapATM: Enhancing HD Map Construction through Actor Trajectory Modeling

arXiv:2604.11081v1 Announce Type: new Abstract: High-definition (HD) mapping tasks, which perform lane detections and predictions, are extremely challenging due to non-ideal conditions such as view oc

Maximum Entropy Relaxation of Multi-Way Cardinality Constraints for Synthetic Population Generation

arXiv:2603.22558v2 Announce Type: replace Abstract: Generating synthetic populations from aggregate statistics is a core component of microsimulation, agent-based modeling, policy analysis, and privac

Research

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

researcharxiv-cs-ai

Optimization-Guided Diffusion for Interactive Scene Generation

arXiv:2512.07661v3 Announce Type: replace Abstract: Realistic and diverse multi-agent driving scenes are crucial for evaluating autonomous vehicles, but safety-critical events which are essential for

safetyarxiv-cs-cv

Perception-aware Exploration for Consumer-grade UAVs

arXiv:2511.14393v2 Announce Type: replace Abstract: In our work, we extend the current state-of-the-art approach for autonomous multi-UAV exploration to consumer-level UAVs, such as the DJI Mini 3 Pro

Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems

arXiv:2604.11807v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems dictates reliance on solar forecasting algorithms that respect atmospheric thermodyna

PokeRL: Reinforcement Learning for Pokemon Red

model-releasesarxiv-cs-lg

arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei

Privacy Against Agnostic Inference Attacks in Vertical Federated Learning

arXiv:2302.05545v4 Announce Type: replace-cross Abstract: A novel form of inference attack in vertical federated learning (VFL) is proposed, where two parties collaborate in training a machine learnin

agentsarxiv-cs-lg

PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving

arXiv:2507.17596v3 Announce Type: replace-cross Abstract: While end-to-end autonomous driving models show promising results, their practical deployment is often hindered by large model sizes, a relian

ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models

model-releasesarxiv-cs-cl

arXiv:2604.09824v1 Announce Type: cross Abstract: Vision language action (VLA) models enable generalist robotic agents but often exhibit language ignorance, relying on visual shortcuts and remaining i

SBAMP: Sampling Based Adaptive Motion Planning

arXiv:2511.12022v2 Announce Type: replace Abstract: Autonomous robots operating in dynamic environments must balance global path optimality with real-time responsiveness to disturbances. This requires

Towards Robust Optimization-Based Autonomous Dynamic Soaring with a Fixed-Wing UAV

arXiv:2512.06610v2 Announce Type: replace Abstract: Dynamic soaring is a flying technique to exploit the energy available in wind shear layers, enabling potentially unlimited flight without the need f

Using Unwrapped Full Color Space Palette Recording to Measure Exposedness of a Vehicle Exterior Parts for External Human Machine Interfaces

arXiv:2604.11406v1 Announce Type: new Abstract: One of the concerns with autonomous vehicles is their ability to communicate their intent to other road users, specially pedestrians, in order to preven

VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG

arXiv:2604.05418v2 Announce Type: replace-cross Abstract: Scaling multimodal large language models (MLLMs) to long videos is constrained by limited context windows. While retrieval-augmented generatio

VLN-NF: Feasibility-Aware Vision-and-Language Navigation with False-Premise Instructions

model-releasesarxiv-cs-cl

arXiv:2604.10533v1 Announce Type: cross Abstract: Conventional Vision-and-Language Navigation (VLN) benchmarks assume instructions are feasible and the referenced target exists, leaving agents ill-equ

All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles

arXiv:2510.26641v4 Announce Type: replace Abstract: Autonomous Vehicles (AVs) are transforming the future of transportation through advances in intelligent perception, decision-making, and control sys

Dejavu: Towards Experience Feedback Learning for Embodied Intelligence

arXiv:2510.10181v3 Announce Type: replace-cross Abstract: Embodied agents face a fundamental limitation: once deployed in real-world environments, they cannot easily acquire new knowledge to improve t

EthicMind: A Risk-Aware Framework for Ethical-Emotional Alignment in Multi-Turn Dialogue

arXiv:2604.09265v1 Announce Type: new Abstract: Intelligent dialogue systems are increasingly deployed in emotionally and ethically sensitive settings, where failures in either emotional attunement or

safetyarxiv-cs-cl

Applications

{sf TriDeliver}: Cooperative Air-Ground Instant Delivery with UAVs, Couriers, and Crowdsourced Ground Vehicles

arXiv:2604.09049v1 Announce Type: new Abstract: Instant delivery, shipping items before critical deadlines, is essential in daily life. While multiple delivery agents, such as couriers, Unmanned Aeria

applicationsarxiv-cs-ro

Sim-to-Real Transfer for Muscle-Actuated Robots via Generalized Actuator Networks

arXiv:2604.09487v1 Announce Type: cross Abstract: Tendon drives paired with soft muscle actuation enable faster and safer robots while potentially accelerating skill acquisition. Still, these systems

safetyarxiv-cs-lg

Before Humans Join the Team: Diagnosing Coordination Failures in Healthcare Robot Team Simulation

arXiv:2508.04691v2 Announce Type: replace-cross Abstract: As humans move toward collaborating with coordinated robot teams, understanding how these teams coordinate and fail is essential for building

Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

arXiv:2604.06173v1 Announce Type: cross Abstract: Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory do

Can VLMs Unlock Semantic Anomaly Detection? A Framework for Structured Reasoning

arXiv:2510.18034v2 Announce Type: replace-cross Abstract: Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emer

Continuous-Time Dynamics of the Difference-of-Convex Algorithm

arXiv:2604.06926v1 Announce Type: cross Abstract: We study the continuous-time structure of the difference-of-convex algorithm (DCA) for smooth DC decompositions with a strongly convex component. In d

agentsarxiv-cs-lg

DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather

arXiv:2604.08074v1 Announce Type: new Abstract: Reliable and weather-robust perception systems are essential for safe autonomous driving and typically employ multi-modal sensor configurations to achie

NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation

arXiv:2406.13086v2 Announce Type: replace Abstract: Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navi

Pseudo-Expert Regularized Offline RL for End-to-End Autonomous Driving in Photorealistic Closed-Loop Environments

arXiv:2512.18662v2 Announce Type: replace-cross Abstract: End-to-end (E2E) autonomous driving models that take only camera images as input and directly predict a future trajectory are appealing for th