Search: “deployment”

Probing Collision Grounding in Vision-Language Models for Safe Human-Robot Collaboration

arXiv:2605.31196v1 Announce Type: cross Abstract: Safe human--robot collaboration requires more than visual description: a monitor must determine whether the robot body is safely separated, already co

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Rethinking Efficient Crack Segmentation with Task-Aligned Structural-Directional Modeling

DGX agent

arXiv:2605.31048v1 Announce Type: new Abstract: Recent crack segmentation methods often follow generic semantic segmentation designs, using stronger backbones, hybrid CNN-Transformer-Mamba encoders, a

local-aiarxiv-cs-cv

1 Jun 2026

Scaling Multi-Agent Environment Co-Design with Diffusion Models

arXiv:2511.03100v2 Announce Type: replace-cross Abstract: The agent-environment co-design paradigm jointly optimises agent policies and environment configurations in search of improved system performa

Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction

arXiv:2605.30593v1 Announce Type: cross Abstract: Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas t

applicationsarxiv-cs-ai

Seeing Before Agreeing: Aligning Multi-Agent Consensus with Visual Evidence

arXiv:2605.30698v1 Announce Type: cross Abstract: Vision-language models (VLMs) have achieved strong performance on visual question answering (VQA). To mitigate individual hallucinations and blind spo

Seeing Fast and Slow: Bimodal 3D Scene Graphs for Open-set Tasks

arXiv:2605.31067v1 Announce Type: new Abstract: Open-set task execution can significantly benefit from seamlessly switching between coarse and fine scene representations depending on the context and t

researcharxiv-cs-ro

SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs

arXiv:2603.20253v2 Announce Type: replace-cross Abstract: Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental reso

Task-Focused Memorization for Multimodal Agents

arXiv:2605.31075v1 Announce Type: new Abstract: Long-term memory is essential for multimodal agents to build coherent experience, accumulate world knowledge, and achieve continual learning. However, c

safetyarxiv-cs-cv

The Architecture of Errors: From Universal Impossibility to Patch-Local LLM Reliability

arXiv:2605.30628v1 Announce Type: cross Abstract: Universal LLM reliability is not a finite-library problem: across all possible tasks, tools, schemas, knowledge sources, and evaluator expectations, n

local-aiarxiv-cs-ai

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics

arXiv:2602.01186v2 Announce Type: replace-cross Abstract: Classical Federated Learning relies on a multi-round iterative process of model exchange and aggregation between server and clients, with high

researcharxiv-cs-ai

The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI

arXiv:2603.00068v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined eve

TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments

arXiv:2602.02459v2 Announce Type: replace Abstract: Robots in dynamic, human-centric environments must follow language instructions while maintaining real-time reactive control. Vision-language-action

researcharxiv-cs-ro

Wall-OSS-0.5 Technical Report

arXiv:2605.30877v1 Announce Type: new Abstract: Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs

safetyarxiv-cs-ro

Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems

arXiv:2506.00175v5 Announce Type: replace-cross Abstract: Modern AI systems are typically developed through multiple stages-pretraining, fine-tuning rounds, and subsequent adaptation or alignment, whe

Accelerating HEVC Intra Partitioning via a CNN-Hierarchical Attention Transformer Hybrid

arXiv:2605.29063v1 Announce Type: cross Abstract: The recursive quad-tree partitioning in High Efficiency Video Coding (HEVC) incurs considerable computational overhead, with exhaustive rate-distortio

local-aiarxiv-cs-cv

Aryabhata 2: Scaling Reinforcement Learning for Advanced STEM Reasoning

arXiv:2605.28829v1 Announce Type: cross Abstract: Competitive STEM examinations such as JEE and NEET require multi-step symbolic reasoning, precise numerical computation, and deep conceptual understan

applicationsarxiv-cs-ai

Auditing Training-Free 3D Shape Retrieval with Diffused Geodesic Moments

model-releasesarxiv-cs-cv

arXiv:2605.29004v1 Announce Type: new Abstract: Reported retrieval scores for training-free shape descriptors conflate local signal design, normalization, aggregation, codebook fitting, and metric cho

Automating Low-Risk Code Review at Meta: RADAR, Risk Calibration, and Review Efficiency

arXiv:2605.30208v1 Announce Type: cross Abstract: AI-assisted coding tools have altered software production. At Meta, significant lines of code per human-landed diff grew by 105.9% year over year and

Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation

arXiv:2605.29560v1 Announce Type: new Abstract: Parameterizing high-fidelity 'digital twins' of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Pre

Ciphera: A Decentralised Biometric Identity Framework

arXiv:2605.29868v1 Announce Type: cross Abstract: Centralised biometric identity systems expose users to single points of failure, opaque verification processes, and irreversible biometric compromise.

applicationsarxiv-cs-cv

CLUBench: A Clustering Benchmark

model-releasesarxiv-cs-lg

arXiv:2605.29933v1 Announce Type: new Abstract: Clustering is a fundamental problem in data science with a long-standing research history, yielding numerous insightful algorithms. Despite this progres

Compass: Navigating Global Marine Lead Data Integration through Expert-Guided LLM Agent

arXiv:2605.29966v1 Announce Type: new Abstract: Marine lead (Pb) and its isotopes are critical tracers for ocean circulation and anthropogenic pollution, yet in-situ observations remain costly and spa

agentsarxiv-cs-ai

DeepFake Forensics AI: A Multi-Modal Detection and Blockchain-Anchored Evidence Management Platform

arXiv:2605.29353v1 Announce Type: cross Abstract: The proliferation of AI-generated synthetic media poses a critical threat to the integrity of digital evidence in legal and forensic contexts. Existin

applicationsarxiv-cs-cv

DeepSurvey: Enhancing Analytical Depth and Citation Reliability in Automated Survey Generation

arXiv:2605.29522v1 Announce Type: new Abstract: As scientific literature grows rapidly, automated survey generation has become a key capability for AI scientists and human researchers. However, existi

DGSG-Mind: Dynamic 3D Gaussian Scene Graphs for Long-Term Scene Understanding and Grounding

arXiv:2605.29879v1 Announce Type: new Abstract: Integrating open-vocabulary semantic information into dynamic 3D scene representations is essential for long-term embodied scene understanding. However,

agentsarxiv-cs-cv

Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption

arXiv:2605.30089v1 Announce Type: new Abstract: Standard Set Representation Learning methods typically excel on curated data but often overlook the challenge of inference-time element corruption. This

researcharxiv-cs-lg

DynaGraph: Lightweight Multi-Model Interaction Framework via Dynamic Topological Reconfiguration

arXiv:2605.29511v1 Announce Type: cross Abstract: Tackling complex reasoning tasks typically relies on massive monolithic LLMs, which suffer from severe computational redundancy. While task decomposit

local-aiarxiv-cs-cl

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing

arXiv:2512.03109v2 Announce Type: replace-cross Abstract: Agentic AI systems execute a sequence of actions, such as reasoning steps or tool calls, in response to a user prompt. To evaluate the success

agentsarxiv-cs-ai

EarthShift: a benchmark for measuring robustness to real-world distribution shifts in Earth observation

model-releasesarxiv-cs-cv

arXiv:2605.29330v1 Announce Type: new Abstract: Current Earth observation benchmarks focus on measuring performance on diverse tasks and applications, typically measuring generalization in-distributio

Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM Conversations

arXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi

Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation

arXiv:2605.29773v1 Announce Type: cross Abstract: Reliable semantic segmentation for mobile robots requires both accurate dense prediction and robust uncertainty estimation under distribution shift. S

applicationsarxiv-cs-ai

Hardware

ESAM++: Efficient Online 3D Perception on the Edge

arXiv:2605.29505v1 Announce Type: new Abstract: Online 3D scene perception in real time is essential for robotics, AR/VR, and autonomous systems, particularly in edge computing scenarios where computa

hardwarearxiv-cs-cv

Evaluation of Conversational Agents: Understanding Culture, Context and Environment in Emotion Detection

arXiv:2605.30099v1 Announce Type: new Abstract: Valuable decisions and highly prioritized analysis now depend on applications such as facial biometrics, social media photo tagging, and human robots in

applicationsarxiv-cs-cv

EXACT-MPPI: Exact Signed-Distance Navigation for Arbitrary-Footprint Robots from Point Clouds via Path Integral Control

arXiv:2605.29663v1 Announce Type: new Abstract: Ground robots often carry payloads, implements, or other attachments that turn their effective footprint into complex, non-convex shapes. Navigating saf

local-aiarxiv-cs-ro

First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope

arXiv:2605.28916v1 Announce Type: cross Abstract: We report a comparison of two state-of-the-art agentic AI systems, Claude Code (Anthropic) and Codex (OpenAI), tasked with autonomously executing a si

From Blind Guess to Informed Judgment: Teaching LLMs to Evaluate Materials by Building Knowledge-Augmented Preference Signals

arXiv:2605.29555v1 Announce Type: new Abstract: As candidate generation and high-throughput experimentation advance, the primary bottleneck in materials discovery is shifting from property prediction

agentsarxiv-cs-cl

Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap

arXiv:2605.28888v1 Announce Type: cross Abstract: Real-world user behavior rarely consists of isolated actions; instead, it often forms intent flows governed by spatiotemporal dependencies. To provide

applicationsarxiv-cs-lg

Gram: Assessing sabotage propensities via automated alignment auditing

arXiv:2605.30322v1 Announce Type: cross Abstract: We introduce Gram, an automated alignment auditing framework to assess the propensity of AI agents to engage in sabotage. We evaluate Gemini models ac

Harmonizing Real-Time Constraints and Long-Horizon Reasoning: An Asynchronous Agentic Framework for Dynamic Scheduling

arXiv:2605.29262v1 Announce Type: new Abstract: The Dynamic Flexible Job Shop Scheduling Problem (DFJSP) necessitates a trade-off between instant reaction to stochastic disturbances and global optimiz

Honeyval: A Comprehensive Evaluation Framework for LLM-powered HTTP Honeypots

arXiv:2605.29963v1 Announce Type: cross Abstract: Honeypots are decoy systems mimicking real system components designed to defend against cyber attacks. Recently, LLMs increasingly serve as simulation

agentsarxiv-cs-ai

How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency

arXiv:2605.30096v1 Announce Type: cross Abstract: Large language models (LLMs) can autonomously conduct multi-stage cyber attacks, but the consistency of their offensive behavior under repeated trials

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models

arXiv:2410.15236v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling app

K-FinHallu: A Hallucination Detection Benchmark for Multi-Turn RAG in Korean Finance

model-releasesarxiv-cs-lg

arXiv:2605.29523v1 Announce Type: new Abstract: Large Language Models (LLMs) have advanced financial automation through Retrieval-Augmented Generation (RAG), yet hallucinations remain a critical barri

KBF: Knowledge Boundary as Fingerprint for Language Model and Black-Box API Auditing

arXiv:2605.29524v1 Announce Type: cross Abstract: Relay and reseller APIs increasingly intermediate access to large language models (LLMs), but users have no direct way to verify that a claimed endpoi

LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs

arXiv:2605.29756v1 Announce Type: new Abstract: As large language models continue to scale, low-bit weight-only post-training quantization (PTQ) offers a practical solution to their memory-efficient d

researcharxiv-cs-ai

LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback

arXiv:2605.30273v1 Announce Type: cross Abstract: Large language models (LLMs) show promise in generating supportive responses for mental health queries, but improving their usefulness, empathy, and s

LUMINA: A Multi-Vendor Mammography Benchmark with Energy Harmonization Protocol

model-releasesarxiv-cs-cv

arXiv:2603.14644v3 Announce Type: replace-cross Abstract: Publicly available full-field digital mammography (FFDM) datasets remain limited in size, clinical annotations, and vendor diversity, hinderin

MARTIAN: A Rendering Framework for Aerial Mars Imagery from HiRISE Orbital Data

arXiv:2605.29647v1 Announce Type: new Abstract: Aerial navigation on Mars requires vision-based pipelines that are robust to the diverse illumination conditions and terrain morphology of the Martian s

researcharxiv-cs-cv