Search: “research”

NavIsaacLab: Generating Realistic Crowd via Parallel Robot Learning for Benchmarking Human-aware Navigation

model-releasesarxiv-cs-ro

arXiv:2606.26265v1 Announce Type: new Abstract: Robot autonomous navigation that accounts for surrounding human activities is crucial for ensuring both safety and natural human-robot interaction in re

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NeuraDock Visual Cognitive Load Agent Tutorial: A Quality-Gated Open-Source EEG Workflow for Alpha Dynamics and Real-Time Applications

DGX agent

arXiv:2606.26518v1 Announce Type: new Abstract: This tutorial paper provides a step-by-step, reproducible walkthrough of NeuraDock Agent, an open-source EEG agent focused on Alpha dynamics and visual

agentsarxiv-cs-ai

26 Jun 2026

Normalizing Flows are Capable Models for Continuous Control

arXiv:2505.23527v4 Announce Type: replace Abstract: Modern reinforcement learning (RL) algorithms have found success by using powerful probabilistic models, such as transformers, energy-based models,

safetyarxiv-cs-lg

Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis

arXiv:2406.10090v3 Announce Type: replace Abstract: Thanks to their extensive capacity, over-parameterized neural networks exhibit superior predictive capabilities and generalization. However, having

PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models

arXiv:2606.26694v1 Announce Type: new Abstract: Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to ex

safetyarxiv-cs-cv

Quantization in Federated Learning: Methods, Challenges and Future Directions

arXiv:2606.26822v1 Announce Type: new Abstract: Federated Learning (FL) has become a foundational paradigm for privacy-preserving distributed intelligence, yet its scalability remains fundamentally co

local-aiarxiv-cs-lg

Radical AI Interpretability

arXiv:2606.26523v1 Announce Type: new Abstract: We develop a framework for interpreting AI systems as agents, drawing on the philosophical tradition of radical interpretation and the tools of mechanis

safetyarxiv-cs-ai

Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints

arXiv:2606.26106v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in emotionally charged situations involving interpersonal conflict, frustration, and distress. Whil

safetyarxiv-cs-ai

Reducing Redundancy in Whole-Slide Image Patching for Scalable Indexing and Retrieval

arXiv:2606.26157v1 Announce Type: cross Abstract: The rapid growth of digital pathology has created an urgent need for efficient indexing and retrieval of whole slide images (WSIs). This need is inten

RedVox: Safety and Fairness Gaps in Speech Models Across Languages

model-releasesarxiv-cs-cl

arXiv:2606.26968v1 Announce Type: new Abstract: Speech-capable models are increasingly deployed in real-world applications across languages. Yet their safety and fairness beyond English settings and u

Tutorials

Scalable Behavior Cloning with Open Data, Training, and Evaluation

arXiv:2606.27375v1 Announce Type: new Abstract: We introduce ABC, a fully open-source stack for manipulation with behavior cloning. At its core is ABC-130K: the largest open-source teleoperation datas

tutorialsarxiv-cs-ro

Scaling Nonlinear Optimization: Many Problems One GPU

arXiv:2606.26341v1 Announce Type: new Abstract: Many robotics problems, including trajectory optimization, inverse kinematics, and contact-rich motion planning, reduce to nonlinear programs (NLPs). Ma

local-aiarxiv-cs-ro

Scientific discovery as meta-optimization: a combinatorial optimization case study

arXiv:2606.26728v1 Announce Type: new Abstract: Scientific discovery is fundamentally an optimization problem, defined by a vast 'state space' of theories and experiments, and an evaluation criterion

ShareLock: A Stealthy Multi-Tool Threshold Poisoning Attack Against MCP

arXiv:2606.27027v1 Announce Type: cross Abstract: With the rapid evolution of LLM-driven agents, Model Context Protocol (MCP), an open protocol bridging LLMs with external tools, has quickly become fo

Towards Video Anomaly Detection from Event Streams: A Baseline and Benchmark Datasets

arXiv:2603.24991v2 Announce Type: replace Abstract: Event-based vision, characterized by low redundancy, focus on dynamic motion, and inherent privacy-preserving properties, naturally fits the demands

UAV-MapFusion: RTK-Aligned Uncertainty-Aware Coarse-to-Fine Multi-Session UAV Mapping

model-releasesarxiv-cs-ro

arXiv:2606.26928v1 Announce Type: new Abstract: Large-scale point cloud maps are essential for robotics and spatial intelligence tasks. UAVs provide an efficient means for large-scale map acquisition;

Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation

arXiv:2606.26984v1 Announce Type: new Abstract: Unified multimodal models capable of both understanding and generation have achieved remarkable strides. However, despite their unified designs, existin

WatchAct: A Benchmark for Behavior-Grounded Robot Manipulation

arXiv:2606.26443v1 Announce Type: cross Abstract: A robot working alongside people must reason about what they have done, in what order, and with what intent. Video carries the spatial layouts, object

2K Retrofit: Entropy-Guided Efficient Sparse Refinement for High-Resolution 3D Geometry Prediction

arXiv:2603.19964v3 Announce Type: replace Abstract: High-resolution geometric prediction is essential for robust perception in autonomous driving, robotics, and AR/MR, but current foundation models ar

A 3D-Printable Dataset for Fair Testing and Comparisons of Tactile Sensors

arXiv:2606.25886v1 Announce Type: cross Abstract: Existing texture datasets for tactile sensing primarily consist of sensor readings from a specific sensor interacting with available surfaces/objects

Auto-Labelling-Based Domain Transfer for 3D Object Detection on a Bicycle-Mounted LiDAR Platform

arXiv:2606.25652v1 Announce Type: new Abstract: Reliable 3D perception of vulnerable road users (VRUs) such as cyclists and pedestrians is essential for their safety in urban traffic and a core requir

Autodata: An agentic data scientist to create high quality synthetic data

arXiv:2606.25996v1 Announce Type: cross Abstract: We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show

agentsarxiv-cs-cl

Automatic Generation of Highlights for Academic Paper Via Prompt-based Learning

arXiv:2606.25253v1 Announce Type: new Abstract: Highlights provide a concise summary of the main contributions of an academic paper and help readers quickly understand its focus. However, many journal

local-aiarxiv-cs-cl

Beyond Defensive Reporting: Machine Learning for Active Anti-Money Laundering Control in Insurance

arXiv:2606.16663v2 Announce Type: replace Abstract: Money laundering through insurance claims poses a threat to insurers both through fraudulent payouts and reputational and regulatory risk. Despite t

applicationsarxiv-cs-lg

Can Trustless Agents Be Trusted? An Empirical Study of the ERC-8004 Decentralized AI Agent Ecosystem

arXiv:2606.26028v1 Announce Type: cross Abstract: As autonomous AI agents increasingly transact across organizational boundaries, a fundamental trust challenge emerges: how can an agent assess whether

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning

arXiv:2510.04773v2 Announce Type: replace Abstract: As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpora, concerns regarding data privacy and safety are receiv

Domain-Specific Agents for Cherenkov Telescope Array Control Software and Gamma-Ray Data Analysis

arXiv:2510.01299v3 Announce Type: replace-cross Abstract: We present domain-adapted large language model agents designed to support Cherenkov Telescope Array operation and data analysis. The agents co

FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming

arXiv:2606.19887v2 Announce Type: replace-cross Abstract: Existing safety benchmarks target general adversarial scenarios but miss finance-specific risks. Financial LLMs face regulatory compliance vio

Geometry-Aware Online Scheduling for LLM Serving: From Theoretical Bound to System Practice

arXiv:2606.22327v2 Announce Type: replace Abstract: The explosive demand for interactive Large Language Model serving has highlighted the management of the Key-Value cache's dynamic memory footprint a

HiT-JEPA: A Hierarchical Self-supervised Trajectory Embedding Framework for Similarity Computation

arXiv:2507.00028v2 Announce Type: replace-cross Abstract: The representation of urban trajectory data plays a critical role in effectively analyzing spatial movement patterns. Despite considerable pro

local-aiarxiv-cs-cv

Homomorphic Encryptions for Privacy Preserving Vision

arXiv:2606.25216v1 Announce Type: cross Abstract: Legal requirements might prevent organizations from sharing sensitive data like medical or financial details of consumers which prevents them from lev

applicationsarxiv-cs-cv

MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Models

model-releasesarxiv-cs-cl

arXiv:2604.05738v2 Announce Type: replace Abstract: Medical Vision-Language Models (Med-VLMs) have achieved expert-level proficiency in interpreting diagnostic imaging. However, current models are pre

Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows

arXiv:2604.25345v2 Announce Type: replace Abstract: Agentic AI systems are increasingly being integrated into scientific workflows, yet their behavior under realistic conditions remains insufficiently

Project Auto-World: Towards Automated Benchmarking of Neural Relational Reasoners

arXiv:2606.24965v1 Announce Type: cross Abstract: Reasoning about relational structures remains a significant challenge for neural models, particularly when they must systematically apply learned know

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems

arXiv:2606.25533v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retri

local-aiarxiv-cs-cl

The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar

arXiv:2606.26015v1 Announce Type: new Abstract: Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities a

safetyarxiv-cs-cl

Toward Low-Latency Vision-Language Models with Doubly-Correct Predictions in Egocentric Visual Understanding

arXiv:2606.25160v1 Announce Type: cross Abstract: The rapid rise of Vision-Language Models (VLMs) in egocentric visual understanding has made low-latency inference in human-robot collaborative (HRC) t

When Multi-Sensor Fusion Fails to Generalize: Cattle Posture Classification Under Animal-Level and Temporal Distribution Shift

arXiv:2606.24986v1 Announce Type: new Abstract: Automated cattle posture-classification systems frequently report near-perfect accuracy, yet their robustness under realistic deployment conditions rema

WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning

model-releasesarxiv-cs-ro

arXiv:2606.25591v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, con

A Paninian Foundation for Indic Language Processing

arXiv:2606.24172v1 Announce Type: cross Abstract: More than a billion people communicate in Indic languages, yet the natural language processing infrastructure serving them remains fragmented and unde

Age of LLM: A Strategic 1v1 Benchmark for Reasoning, Diplomacy and Reliability of Large Language Models under Fog of War

arXiv:2606.24391v1 Announce Type: new Abstract: We introduce Age of LLM, a turn-based 1v1 benchmark in which two LLMs face off on a 13x7 grid to destroy the enemy base. Three stressors are deliberate:

AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models

arXiv:2606.24616v1 Announce Type: new Abstract: Tokens have become the practical accounting unit for modern foundation model services, linking information processing, computation, memory use, energy e

Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications

arXiv:2606.23858v1 Announce Type: cross Abstract: A primary challenge in AI safety is the existence of adversarial examples -- slightly distorted inputs that cause a neural network (NN) to misclassify

safetyarxiv-cs-ai

Best Preprocessing Techniques for Sentiment Analysis

arXiv:2606.24055v1 Announce Type: new Abstract: Sentiment analysis in Twitter datasets is important because it enables monitoring public opinion on products and analysis of political and social moveme

applicationsarxiv-cs-cl

Decentralized Coordination of Autonomous Traffic Through Advanced Air Mobility Corridors

arXiv:2606.23832v1 Announce Type: cross Abstract: The use of dedicated corridors for Advanced Air Mobility (AAM) traffic is one of the most commonly proposed pathways to integrating them into existing

Ensemble Learning for Large Language Models in Text and Code Generation: A Survey

arXiv:2503.13505v3 Announce Type: replace-cross Abstract: Generative Pretrained Transformers (GPTs) are foundational Large Language Models (LLMs) for text generation. However, individual LLMs often pr

Fabric Image Demoireing Benchmark from Synthesis to Restoration

arXiv:2606.24072v1 Announce Type: new Abstract: Fabric moire is a sampling-induced aliasing artifact caused by the interaction between fine textile patterns and camera sensor grids, producing structur

Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings

arXiv:2505.13087v2 Announce Type: replace-cross Abstract: We propose a novel benchmarking methodology for graph neural networks (GNNs) based on the graph alignment problem, a combinatorial optimizatio