Search: “agents”

Sixth-Sense: Self-Supervised Learning of Spatial Awareness of Humans from a Planar Lidar

arXiv:2502.21029v2 Announce Type: replace-cross Abstract: Reliable localization of people is fundamental for service and social robots that must operate in close interaction with humans. State-of-the-

local-aiarxiv-cs-lg

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Safety

StoryCoder: Narrative Reformulation for Structured Reasoning in LLM Code Generation

DGX agent

arXiv:2604.14631v1 Announce Type: new Abstract: Effective code generation requires both model capability and a problem representation that carefully structures how models reason and plan. Existing app

safetyarxiv-cs-cl

17 Apr 2026

The Cost of Language: Centroid Erasure Exposes and Exploits Modal Competition in Multimodal Language Models

arXiv:2604.14363v1 Announce Type: new Abstract: Multimodal language models systematically underperform on visual perception tasks, yet the structure underlying this failure remains poorly understood.

local-aiarxiv-cs-cl

TOPCELL: Topology Optimization of Standard Cell via LLMs

arXiv:2604.14237v1 Announce Type: new Abstract: Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability.

safetyarxiv-cs-lg

Trajectory Planning for a Multi-UAV Rigid-Payload Cascaded Transportation System Based on Enhanced Tube-RRT*

arXiv:2604.15074v1 Announce Type: new Abstract: This paper presents a two-stage trajectory planning framework for a multi-UAV rigid-payload cascaded transportation system, aiming to address planning c

Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization

arXiv:2604.15196v1 Announce Type: new Abstract: We propose a novel hierarchical spatiotemporal vector quantization framework for unsupervised skeleton-based temporal action segmentation. We first intr

V-Reflection: Transforming MLLMs from Passive Observers to Active Interrogators

arXiv:2604.03307v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success, yet they remain prone to perception-related hallucinations in fine-graine

local-aiarxiv-cs-cv

Hardware

Automatic Charge State Tuning of 300 mm FDSOI Quantum Dots Using Neural Network Segmentation of Charge Stability Diagram

arXiv:2604.13662v1 Announce Type: cross Abstract: Tuning of gate-defined semiconductor quantum dots (QDs) is a major bottleneck for scaling spin qubit technologies. We present a deep learning (DL) dri

hardwarearxiv-cs-cv

Capability-Aware Heterogeneous Control Barrier Functions for Decentralized Multi-Robot Safe Navigation

arXiv:2604.13245v1 Announce Type: new Abstract: Safe navigation for multi-robot systems requires enforcing safety without sacrificing task efficiency under decentralized decision-making. Existing dece

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation

model-releasesarxiv-cs-cl

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

Drowsiness-Aware Adaptive Autonomous Braking System based on Deep Reinforcement Learning for Enhanced Road Safety

model-releasesarxiv-cs-lg

arXiv:2604.13878v1 Announce Type: new Abstract: Driver drowsiness significantly impairs the ability to accurately judge safe braking distances and is estimated to contribute to 10%-20% of road acciden

Failure Identification in Imitation Learning Via Statistical and Semantic Filtering

arXiv:2604.13788v1 Announce Type: cross Abstract: Imitation learning (IL) policies in robotics deliver strong performance in controlled settings but remain brittle in real-world deployments: rare even

Foresight Optimization for Strategic Reasoning in Large Language Models

arXiv:2604.13592v1 Announce Type: new Abstract: Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-ba

Jump-Start Reinforcement Learning with Vision-Language-Action Regularization

arXiv:2604.13733v1 Announce Type: new Abstract: Reinforcement learning (RL) enables high-frequency, closed-loop control for robotic manipulation, but scaling to long-horizon tasks with sparse or imper

safetyarxiv-cs-lg

MDPs with a State Sensing Cost

model-releasesarxiv-cs-lg

arXiv:2505.03280v3 Announce Type: replace Abstract: In many practical sequential decision-making problems, tracking the state of the environment incurs a sensing/communication/computation cost. In the

PersonaVLM: Long-Term Personalized Multimodal LLMs

model-releasesarxiv-cs-cl

arXiv:2604.13074v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) serve as daily assistants for millions. However, their ability to generate responses aligned with individual pr

Reducing Hallucinations in LLMs via Factuality-Aware Preference Learning

arXiv:2601.03027v3 Announce Type: replace Abstract: Preference alignment methods such as RLHF and Direct Preference Optimization (DPO) improve instruction following, but they can also reinforce halluc

Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers

arXiv:2509.07464v2 Announce Type: replace Abstract: Autonomous vehicles must navigate dynamically uncertain environments while balancing safety and efficiency. This challenge is exacerbated by unpredi

See&Say: Vision Language Guided Safe Zone Detection for Autonomous Package Delivery Drones

arXiv:2604.13292v1 Announce Type: new Abstract: Autonomous drone delivery systems are rapidly advancing, but ensuring safe and reliable package drop-offs remains highly challenging in cluttered urban

Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization

arXiv:2604.13197v1 Announce Type: new Abstract: Process reward models (PRMs) provide fine-grained reward signals along the reasoning process, but training reliable PRMs often requires step annotations

local-aiarxiv-cs-cl

WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain

model-releasesarxiv-cs-cl

arXiv:2604.13055v1 Announce Type: new Abstract: Today's evolving labor markets rely increasingly on recommender systems for hiring, talent management, and workforce analytics, with natural language pr

Active Imitation Learning for Thermal- and Kernel-Aware LFM Inference on 3D S-NUCA Many-Cores

arXiv:2604.11948v1 Announce Type: new Abstract: Large Foundation Model (LFM) inference is both memory- and compute-intensive, traditionally relying on GPUs. However, the limited availability and high

safetyarxiv-cs-lg

BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH

arXiv:2604.12005v1 Announce Type: cross Abstract: Bayesian optimization (BO) has for sequential optimization of expensive black-box functions demonstrated practicality and effectiveness in many real-w

Benchmarking Deflection and Hallucination in Large Vision-Language Models

arXiv:2604.12033v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) increasingly rely on retrieval to answer knowledge-intensive multimodal questions. Existing benchmarks overlook c

BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

arXiv:2604.11861v1 Announce Type: new Abstract: Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. I

local-aiarxiv-cs-ro

Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks

arXiv:2604.12325v1 Announce Type: cross Abstract: We consider the problem of offline black-box optimization, where the goal is to discover optimal designs (e.g., molecules or materials) from past expe

Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining

arXiv:2604.12683v1 Announce Type: new Abstract: Current fMRI foundation models primarily rely on a limited range of brain states and mismatched pretraining tasks, restricting their ability to learn ge

Contextual Multi-Task Reinforcement Learning for Autonomous Reef Monitoring

arXiv:2604.12645v1 Announce Type: cross Abstract: Although autonomous underwater vehicles promise the capability of marine ecosystem monitoring, their deployment is fundamentally limited by the diffic

Research

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation

arXiv:2604.12424v1 Announce Type: cross Abstract: Multimodal Large Language Models frequently suffer from inference hallucinations, partially stemming from language priors dominating visual evidence.

researcharxiv-cs-ai

DeCoNav: Dialog enhanced Long-Horizon Collaborative Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2604.12486v1 Announce Type: new Abstract: Long-horizon collaborative vision-language navigation (VLN) is critical for multi-robot systems to accomplish complex tasks beyond the capability of a s

Tutorials

Designing for Error Recovery in Human-Robot Interaction

arXiv:2604.12473v1 Announce Type: new Abstract: This position paper looks briefly at the way we attempt to program robotic AI systems. Many AI systems are based on the idea of trying to improve the pe

tutorialsarxiv-cs-ro

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

arXiv:2604.12812v1 Announce Type: new Abstract: Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document le

Research

Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising

arXiv:2604.12799v1 Announce Type: cross Abstract: The rise of automated bidding strategies in online advertising presents new challenges in designing and analyzing efficient auction mechanisms. In thi

researcharxiv-cs-ai

Evaluating Language Models for Harmful Manipulation

arXiv:2603.25326v4 Announce Type: replace Abstract: Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a f

Grasp in Gaussians: Fast Monocular Reconstruction of Dynamic Hand-Object Interactions

arXiv:2604.12929v1 Announce Type: new Abstract: We present Grasp in Gaussians (GraG), a fast and robust method for reconstructing dynamic 3D hand-object interactions from a single monocular video. Unl

HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models

arXiv:2604.12229v1 Announce Type: new Abstract: Small language models (SLMs) often struggle with complex mathematical reasoning due to limited capacity to maintain long chains of intermediate steps an

HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing

arXiv:2604.12331v1 Announce Type: new Abstract: LiDAR semantic segmentation plays a pivotal role in 3D scene understanding for edge applications such as autonomous driving. However, significant challe

local-aiarxiv-cs-cv

Improved particle swarm optimization algorithm: multi-target trajectory optimization for swarm drones

arXiv:2507.13647v2 Announce Type: replace-cross Abstract: Real-time trajectory planning for unmanned aerial vehicles (UAVs) in dynamic environments remains a key challenge due to high computational de

LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety

arXiv:2604.12710v1 Announce Type: cross Abstract: Large language models (LLMs) often demonstrate strong safety performance in high-resource languages, yet exhibit severe vulnerabilities when queried i

LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Software

arXiv:2604.12994v1 Announce Type: cross Abstract: Logical vulnerabilities in software stem from flaws in program logic rather than memory safety, which can lead to critical security failures. Although

Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning

arXiv:2604.12479v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major cha

MoDora: Tree-Based Semi-Structured Document Analysis System

arXiv:2602.23061v3 Announce Type: replace-cross Abstract: Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and

Operationalising the Right to be Forgotten in LLMs: A Lightweight Sequential Unlearning Framework for Privacy-Aligned Deployment in Politically Sensitive Environments

arXiv:2604.12459v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in politically sensitive environments, where memorisation of personal data or confidential conten

PAINT: Partner-Agnostic Intent-Aware Cooperative Transport with Legged Robots

arXiv:2604.12852v1 Announce Type: new Abstract: Collaborative transport requires robots to infer partner intent through physical interaction while maintaining stable loco-manipulation. This becomes pa

PR-MaGIC: Prompt Refinement Via Mask Decoder Gradient Flow For In-Context Segmentation

arXiv:2604.12113v1 Announce Type: cross Abstract: Visual Foundation Models (VFMs) such as the Segment Anything Model (SAM) have significantly advanced broad use of image segmentation. However, SAM and

ReflectCAP: Detailed Image Captioning with Reflective Memory

arXiv:2604.12357v1 Announce Type: new Abstract: Detailed image captioning demands both factual grounding and fine-grained coverage, yet existing methods have struggled to achieve them simultaneously.

RePAIR: Interactive Machine Unlearning through Prompt-Aware Model Repair

arXiv:2604.12820v1 Announce Type: new Abstract: Large language models (LLMs) inherently absorb harmful knowledge, misinformation, and personal data during pretraining on large-scale web corpora, with

Retrieval as a Decision: Training-Free Adaptive Gating for Efficient RAG

arXiv:2511.09803v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) improves factuality but retrieving for every query often hurts quality while inflating tokens and latency. We p