Search: “applications”

SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.10305v1 Announce Type: new Abstract: Fine-tuning vision-language-action (VLA) policies for long-horizon manipulation still relies heavily on behavior cloning, which requires costly high-qua

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Tutorials

Spatiotemporal Graph Transformer for 3D Neighborhood Interaction and Quality Prediction in Metal Additive Manufacturing

DGX agent

arXiv:2606.10227v1 Announce Type: new Abstract: Metal additive manufacturing enables the fabrication of complex parts, but achieving consistent build quality remains challenging due to interactions in

tutorialsarxiv-cs-lg

10 Jun 2026

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation

arXiv:2606.10749v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly moving from conversational interfaces to software components that plan, invoke tools, maintain memory, a

agentsarxiv-cs-ai

Uncertainty-aware Multi-fidelity Closure via Conditional Normalizing Flows

arXiv:2606.09857v1 Announce Type: new Abstract: Reduced-order models (ROMs) provide an efficient surrogate for complex multiscale systems, but their predictive accuracy is often compromised by truncat

UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors

arXiv:2606.11131v1 Announce Type: new Abstract: Most existing deep learning-based PET image denoising methods assume a fixed and known dose reduction factor (DRF) for low-dose PET images. However, the

safetyarxiv-cs-cv

Unleashing Correlation and Continuity for Hyperspectral Reconstruction from RGB Images

arXiv:2501.01481v2 Announce Type: replace-cross Abstract: Reconstructing Hyperspectral Images (HSI) from RGB images can yield high spatial resolution HSI at a lower cost, demonstrating significant app

local-aiarxiv-cs-cv

Upper Bounds for Local Learning Coefficients of Three-Layer Neural Networks

arXiv:2603.12785v2 Announce Type: replace Abstract: Three-layer neural networks are known to form singular learning models, and their Bayesian asymptotic behavior is governed by the learning coefficie

V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions

arXiv:2512.11995v2 Announce Type: replace-cross Abstract: While many vision-language models (VLMs) are developed to answer well-defined, straightforward questions with highly specified targets, as in

Vehicle Prediction Model for Enhanced MPC Path Tracking in Formula Student Driverless

arXiv:2606.10732v1 Announce Type: new Abstract: Autonomous race cars, such as in Formula Student Driverless, operate close to their physical handling limits. The resulting highly nonlinear vehicle beh

agentsarxiv-cs-ro

Workflow-GYM: Towards Long-Horizon Evaluation of Computer-use Agentic tasks in Real-World Professional Fields

arXiv:2606.11042v1 Announce Type: new Abstract: Recent years have witnessed the rapid evolution of AI agents toward handling increasingly complex, real-world tasks. However, existing benchmarks rarely

You can now use your favourite VSC themes inside of Hermes Desktop @NousResearch

Nous Research announced that VSCode themes are now compatible with Hermes Desktop, allowing users to apply their preferred Visual Studio Code themes to the Hermes Desktop environment. This enhancement

researchnous-research--x

A Camera-Native Talking-Head Video Dataset for Various Computer Vision Tasks

arXiv:2603.26763v2 Announce Type: replace Abstract: Talking-head videos constitute a predominant content type in real-time communication, yet publicly available datasets for video processing research

researcharxiv-cs-cv

A generalizable 3D framework and model for self-supervised learning in medical imaging

arXiv:2501.11755v2 Announce Type: replace-cross Abstract: Current self-supervised learning methods for 3D medical imaging rely on simple pretext formulations and organ- or modality-specific datasets,

researcharxiv-cs-cv

A Geometric Measure of Linear Separability for Neural Representations

arXiv:2606.08721v1 Announce Type: new Abstract: Modern neural classifiers commonly rely on linear readouts, yet predictive metrics alone do not characterize the class-wise geometry of the representati

A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2510.26307v3 Announce Type: replace-cross Abstract: Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essent

AccioScene: Compositional 3D Scene Generation via Graph Diffusion and Interaction-driven Critics

arXiv:2502.06819v2 Announce Type: replace Abstract: This paper presents a framework for generating 3D indoor scenes from text prompts. Existing methods often formulate scene synthesis as an object lay

Adaptive Loss Balancing for Noise-Robust GRPO in Generative Recommendation

arXiv:2606.08480v1 Announce Type: cross Abstract: Reinforcement learning (RL) presents a promising avenue for enhancing generative recommendation beyond supervised imitation, leveraging reward signals

safetyarxiv-cs-ai

Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder

arXiv:2412.06147v2 Announce Type: replace Abstract: For the early identification, diagnosis, and treatment of mental health illnesses, the integration of deep learning (DL) and machine learning (ML) h

Agent filesystems are the new RAG It seems like this pattern is around to stay and will only get more robust over time. Agents need tools to…

Agent filesystems are the new RAG It seems like this pattern is around to stay and will only get more robust over time. Agents need tools to not only read and search over documents, but an entire infr

agentsjerry-liu--x

AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library

arXiv:2510.18428v4 Announce Type: replace Abstract: Optimization modeling underlies critical decision-making across industries, yet remains difficult to automate: natural-language problem descriptions

Industry

Announcing the 2026 Databricks Customer Awards Industry winners

Databricks announced the winners of its 2026 Customer Awards, which recognize outstanding achievements and innovation by Databricks customers across various industries. The awards highlight organizati

industrydatabricks

Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach

arXiv:2507.12843v3 Announce Type: replace Abstract: Are two distributions close to each other with statistical significance? Distribution closeness testing (DCT) formalizes this question by testing wh

Assessing Sample Quality in Conditional Generation under Compositional Shift

arXiv:2606.09601v1 Announce Type: new Abstract: Conditional generators provide a natural tool for controllable generation, including settings where the desired condition is a new composition of observ

Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound

arXiv:2502.16584v2 Announce Type: replace-cross Abstract: Recent advancements in audio tokenization have significantly enhanced the integration of audio capabilities into large language models (LLMs).

Beyond Accuracy: Interpreting Topic Representation in Suicide Ideation Detection Models

arXiv:2606.07714v1 Announce Type: cross Abstract: Suicide ideation detection models are typically evaluated using aggregate performance metrics, yet little is known about how they internally represent

safetyarxiv-cs-ai

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching

arXiv:2411.16102v2 Announce Type: replace Abstract: Offline batch inference, which leverages the flexibility of request batching to achieve higher throughput and lower costs, is becoming more popular

Bokeh Diffusion: Defocus Blur Control in Text-to-Image Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2503.08434v5 Announce Type: replace-cross Abstract: Recent advances in large-scale text-to-image models have revolutionized creative fields by generating visually captivating outputs from textua

Hardware

BRAIN: Bayesian Reasoning via Active Inference for Agentic and Embodied Intelligence in Mobile Networks

arXiv:2602.14033v1 Announce Type: cross Abstract: Future sixth-generation (6G) mobile networks will demand artificial intelligence (AI) agents that are not only autonomous and efficient, but also capa

hardwarearxiv-cs-ai

Breaking the Tokenizer Barrier: On-Policy Distillation across Model Families

arXiv:2606.09456v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has become a core technique in the post-training of Large Language Models (LLMs) for transferring knowledge from domain exp

safetyarxiv-cs-lg

CamoSAM2: SAM2-oriented Prompt Auto-Refinement for Video Camouflaged Object Detection

model-releasesarxiv-cs-cv

arXiv:2504.00375v2 Announce Type: replace Abstract: The Segment Anything Model 2 (SAM2), a prompt-guided video foundation model, has remarkably performed in video object segmentation, drawing signific

Causal Representation Learning from Network Data

arXiv:2509.01916v2 Announce Type: replace Abstract: Causal disentanglement from soft interventions is identifiable under the assumptions of linear interventional faithfulness and availability of both

Claude Fable 5 now available on AI Gateway

model-releasesvercel-blog

Claude Fable 5 is now available through Vercel's AI Gateway, expanding the model options developers can access through the platform. This announcement likely details how developers can integrate and u

Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning

arXiv:2606.09138v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has become an important post-training paradigm for turning LLMs from static chatbots into interactive agents, giving

safetyarxiv-cs-lg

Collaborative Human-Agent Protocol (CHAP)

arXiv:2606.09751v1 Announce Type: new Abstract: Foundation models are moving from response generation into operational roles. They plan across steps, call tools, request human input, coordinate with o

agentsarxiv-cs-ai

Communication-Efficient Federated Learning under Dynamic Device Arrival and Departure: Convergence Analysis and Algorithm Design

arXiv:2410.05662v4 Announce Type: replace Abstract: Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or leavin

local-aiarxiv-cs-lg

Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering

arXiv:2602.17911v3 Announce Type: replace-cross Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is

Crop Recommendation and Agricultural Query Answering System Using Spatio-Temporal Graph Neural Networks and Hybrid Retrieval Augmentation

arXiv:2606.09160v1 Announce Type: cross Abstract: This paper presents a unified system designed to support precision agriculture by integrating advanced weather prediction, crop recommendation, and a

Data-driven discovery of governing differential equations across physical systems

arXiv:2606.09638v1 Announce Type: new Abstract: Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical

Deep Tree Tensor Networks

arXiv:2502.09928v2 Announce Type: replace-cross Abstract: Originating in quantum physics, tensor networks (TNs) have been widely adopted as exponential machines and parametric decomposers for recognit

DN-Hypo-Pipeline: An AI-Driven Workflow for Hypothesis Generation via Large Language Models and Scientific Explanations

arXiv:2606.08532v1 Announce Type: new Abstract: A scientific hypothesis is the first step in research and undergoes experimental validation, yet it also reflects a deep understanding of and reasoning

DTEX adds AI Risk Management to track how agents and employees use AI

Behavioral intelligence security company DTEX Systems Inc. today introduced an expanded AI Risk Management product that reads the intent behind how employees and autonomous artificial intelligence age

agentssiliconangle

Efficient Traffic Prediction at Scale: A Systematic Study of STGCN Architectural Depth

arXiv:2606.09539v1 Announce Type: new Abstract: Spatio-temporal graph neural networks (STGNNs) have become the dominant approach for traffic prediction, yet their computational requirements pose chall

Empowering Feed-Forward Reconstruction Models with Metric Scale via Satellite Images

arXiv:2606.08205v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models have recently shown strong generalization across diverse scenes, yet most of them recover geometry only up to an u

local-aiarxiv-cs-cv

Enhancing Adversarial Robustness with Signed Distance Fields for Harmonizing Geometric Invariance and Texture

arXiv:2602.05175v2 Announce Type: replace Abstract: Deep neural networks demonstrate impressive performance in visual recognition but remain highly vulnerable to imperceptible adversarial attacks. Exi

local-aiarxiv-cs-cv

Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones

arXiv:2507.00322v2 Announce Type: replace-cross Abstract: Despite remarkable advances in coding capabilities, language models (LMs) still struggle with simple syntactic tasks such as generating balanc

Forecasting Japanese elections: A nonlinear machine-learning approach

arXiv:2606.07572v1 Announce Type: cross Abstract: Despite Japan being one of the world's largest advanced democracies, the development of election forecasting models for its national elections remains

Forward-Looking Stress Testing Under Macro Scenarios: Stable SVaR Estimation Using a Hybrid GPR-HS Framework with SACS

arXiv:2606.07575v1 Announce Type: cross Abstract: Regulatory stress testing frameworks, including the Comprehensive Capital Analysis and Review (CCAR) and the Internal Capital Adequacy Assessment Proc

From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction

arXiv:2606.09392v1 Announce Type: new Abstract: Efficient acquisition, storage, and utilization of traffic data are critical challenges in spatio-temporal data management. Most traffic data systems co