Search: “deployment”

A study on a Real-Time VR-Based Teleoperation Framework for Manipulator in Dynamic Environment

arXiv:2605.30989v1 Announce Type: new Abstract: Robot teleoperation enables safe, non-contact task execution in hazardous environments where direct human access is difficult, and its application has e

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Agents

AgentOps: Operationalize agentic AI at scale with Amazon Bedrock AgentCore

DGX agent

When you build agentic AI solutions, you face unique operational challenges. Agents make unpredictable decisions, costs spiral unexpectedly, and debugging non-deterministic failures seems impossible.

agentsaws-ml-blog

1 Jun 2026

An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations

arXiv:2605.30604v1 Announce Type: cross Abstract: Regulated cybersecurity workflows lack a runtime substrate that enforces organization-level scope across retrieval, tool calls, memory, findings, repo

local-aiarxiv-cs-ai

Anchoring LLM Gender Bias to Human Baselines: A Cross-Lingual Audit

model-releasesarxiv-cs-cl

arXiv:2605.30804v1 Announce Type: new Abstract: We audit six large language models (LLMs) for gender stereotyping across English, Korean, Chinese, and Japanese. Three were developed primarily for Engl

Before Parc Ferme: RL-Time Pruning for Efficient Embodied LLMs in Autonomous Driving

arXiv:2605.31256v1 Announce Type: new Abstract: Embodied Large Language Models (LLMs) are increasingly used as reasoning modules in robotic control pipelines to improve human-robot interaction, but th

agentsarxiv-cs-ro

Beyond LLMs: Why Scalable Enterprise AI Adoption Depends on Agent Logic

Enterprise AI adoption at scale requires moving beyond large language models to implement agent logic systems that can handle complex reasoning, planning, and decision-making autonomously. Agent-based

agentshugging-face

Beyond Memorization: Assessing Semantic Generalization in Large Language Models Using Phrasal Constructions

arXiv:2501.04661v3 Announce Type: replace-cross Abstract: The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represente

COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation

arXiv:2605.31264v1 Announce Type: new Abstract: LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and in

CoMem: Context Management with A Decoupled Long-Context Model

arXiv:2605.30842v1 Announce Type: new Abstract: Context management enables agentic models to solve long-horizon tasks through iterative summarization of previous interaction histories. However, this p

agentsarxiv-cs-lg

Connecting agents directly to Snowflake, Slack, or BigQuery via MCP/CLIs is a multi-token disaster. They default to brute-force exploration,…

Connecting agents directly to Snowflake, Slack, or BigQuery via MCP/CLIs is a multi-token disaster. They default to brute-force exploration, firing 20-30 tool calls just to rediscover context on every

agentspinecone--x

Consolidating Rewarded Perturbations for LLM Post-Training

arXiv:2605.31494v1 Announce Type: new Abstract: Post-training of language models is commonly framed as a sample-score-update loop implemented by gradient descent. A recent line of work, exemplified by

researcharxiv-cs-cl

Hardware

Develop Physical AI Reasoning, World, and Action Models with NVIDIA Cosmos 3

NVIDIA Cosmos 3 is a frontier foundation model for physical AI that combines physical reasoning, world generation, and action generation within a single open model. The model uses a Mixture-of-Transfo

hardwarenvidia-developer

Developing a UXR Point of View for Cognitive Accessibility in Mobile Learning with Generative AI

arXiv:2605.31149v1 Announce Type: cross Abstract: This study investigates how UX research (UXR) principles, combined with Large Language Model (LLM)-supported analysis, can be used to improve the qual

researcharxiv-cs-ai

Diving into Kronecker Adapters: Component Design Matters

model-releasesarxiv-cs-lg

arXiv:2602.01267v2 Announce Type: replace Abstract: Kronecker adapters have emerged as a promising approach for fine-tuning large-scale models, enabling high-rank updates through tunable component str

DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrieval

arXiv:2605.31377v1 Announce Type: cross Abstract: Agentic Retrieval-Augmented Generation improves retrieval by integrating planning, tool use, and iterative reasoning, but existing agentic RAG methods

Hardware

Elastic ViTs from Pretrained Models without Retraining

arXiv:2510.17700v2 Announce Type: replace Abstract: Vision foundation models achieve remarkable performance but are only available in a limited set of pre-determined sizes, forcing sub-optimal deploym

hardwarearxiv-cs-cv

Evaluating using Mock Tool Calls to Quarantine Untrusted Prompt Inputs

arXiv:2605.30521v1 Announce Type: new Abstract: Large language models must frequently process untrusted inputs, such as judging an answer from another model or running tasks like spam and harm classif

researcharxiv-cs-cl

Feature-Optimized Vision for Adaptive 3D Scene Reconstruction

arXiv:2605.31534v1 Announce Type: cross Abstract: Three-dimensional scene reconstruction depends on local image evidence that is both visually discriminative and geometrically useful. Fixed feature th

safetyarxiv-cs-ai

Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA

arXiv:2605.31064v1 Announce Type: cross Abstract: Large Language Models (LLMs) have significantly advanced online data services, particularly in the domain of financial question answering (FinQA). How

GETA: Generalized Encrypted Traffic Analysis

arXiv:2605.31277v1 Announce Type: cross Abstract: Traditional traffic analysis is being fundamentally challenged by the rapid adoption of encryption, tunnelling, and privacy-preserving protocols, whic

researcharxiv-cs-lg

Tutorials

Haptic Sorter: A Unified Planning Framework for Online Shape Estimation and Real-Time Pose Inference

arXiv:2605.31352v1 Announce Type: new Abstract: Robotics manipulation usually assumes that the shape and pose of the object are known to the robot prior to motion planning. However, precise geometric

tutorialsarxiv-cs-ro

Tutorials

here's a quick overview of a) what is deepagents b) what makes deepagents good at complex tasks c) how to easily take one to production! htt…

tutorialsharrison-chase--x

DeepAgents are AI systems designed to handle complex tasks through advanced reasoning and planning capabilities. The post outlines the key features that enable DeepAgents to excel at complicated probl

Hermes Agent is now natively supported on @Windows

Nous Research announced native support for Hermes Agent on Windows, expanding the availability of their Hermes model to Windows-based systems. This development enables Windows users to run Hermes Agen

agentsnous-research--x

Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness

arXiv:2605.30745v1 Announce Type: new Abstract: Large Vision-Language Models have achieved unprecedented success in zero-shot recognition by aligning visual features with broad semantic concepts. Howe

researcharxiv-cs-cv

Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search

model-releasesarxiv-cs-cv

arXiv:2605.30917v1 Announce Type: cross Abstract: As large-scale visual-document corpora such as arXiv papers and enterprise PDFs continue to grow, visual-document retrieval has gained increasing atte

Intel touts 130-plus edge design wins for Series 3 and launches OpenVINO Physical AI framework

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Intel Corp. today announced that more than 130 design engagements for its Series 3 processor family for edge artificial intelligence and edge computing designs and also unveiled a new open-source fram

Investigating Detection and Obfuscation of Prompt Injection Attacks Against Software Reverse Engineering AI Agents

arXiv:2605.30677v1 Announce Type: cross Abstract: Agentic software reverse engineering systems are vulnerable to prompt injection attacks placed into the source code of executable binary files. This r

Learning Terrain-Aware Whole-Body Control for Perceptive Legged Loco-Manipulation

arXiv:2605.31343v1 Announce Type: new Abstract: Legged manipulators integrate exceptional terrain adaptability along with mobile manipulation capabilities, which make them highly promising for deploym

safetyarxiv-cs-ro

LLM-FACETS: A Privacy-Preserving Framework for Evaluating LLM Transparency and Accountability

arXiv:2605.31167v1 Announce Type: new Abstract: Assessing whether Large Language Models outputs are factually grounded, epistemically calibrated, and methodologically reproducible is a prerequisite fo

local-aiarxiv-cs-ai

Tutorials

LPTR-AFLNet: Lightweight Integrated Chinese License Plate Rectification and Recognition Network

arXiv:2507.16362v3 Announce Type: replace Abstract: Chinese License Plate Recognition (CLPR) faces numerous challenges in unconstrained and complex environments, particularly due to perspective distor

tutorialsarxiv-cs-cv

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks

arXiv:2603.02630v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved great success in many real-world applications, especially the one serving as the cognitive backbone

MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding

arXiv:2605.30794v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant achievements in general visual question answering (VQA) tasks. However, they re

Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode

arXiv:2605.30571v1 Announce Type: cross Abstract: Physical AI systems, including robots, autonomous vehicles, embodied agents and edge copilots, often run a different inference workload from cloud LLM

Nemotron 3 Ultra: Frontier smart. 5X faster. 30% cheaper. 💚💚💚

model-releasesjeremy-howard--x

Nemotron 3 Ultra is NVIDIA's latest language model featuring significant improvements in speed (5X faster) and cost efficiency (30% cheaper) compared to previous versions, positioning it as a frontier

NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving

arXiv:2605.31116v1 Announce Type: new Abstract: Recent perception-free end-to-end (E2E) autonomous driving methods bypass explicit perception outputs by compressing dense image patch tokens into compa

agentsarxiv-cs-cv

On-Device Generative AI for GDPR-Compliant Visual Monitoring: Natural Language Alerts from Local Object Detection

model-releasesarxiv-cs-cv

arXiv:2605.30544v1 Announce Type: new Abstract: Visual monitoring systems that rely on cloud-based AI inference expose raw image data to external services, creating fundamental tensions with the data-

On-Device Robotic Planning: Eliminating Inference Redundancy for Efficient Decision-Making

arXiv:2605.31460v1 Announce Type: new Abstract: Reasoning-based robotic policies using large language and vision-language models achieve strong semantic planning capabilities but mostly suffer from a

local-aiarxiv-cs-ro

Positional versus Symbolic Attention Heads: Learning Dynamics, RoPE Geometry, and Length Generalization

arXiv:2605.31558v1 Announce Type: cross Abstract: Transformer-based language models are widespread in today's society. As such, understanding the mechanisms by which they solve structured tasks and pr

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

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

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

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

safetyarxiv-cs-ai

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

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

safetyarxiv-cs-ai

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