Search: “deployment”

Breaking Diversity Collapse in Spiking Pseudo-Ensembles for Efficient OOD Detection in Remote Sensing

arXiv:2608.01090v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) are attractive for resource-constrained remote-sensing systems, but reliable out-of-distribution (OOD) detection remains

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BRiG-AFA: Bellman Risk-to-Go Learning for Non-Myopic Active Feature Acquisition

DGX agent

arXiv:2608.02305v1 Announce Type: new Abstract: Active feature acquisition (AFA) asks which unobserved feature to measure next for each test instance under a budget. Greedy rules are easy to train but

model-releasesarxiv-cs-lg

4 Aug 2026

Building agents that patch other agents. This is an interesting approach for self-improving agents that leverages agent outputs. If you run …

Building agents that patch other agents. This is an interesting approach for self-improving agents that leverages agent outputs. If you run agents in production, you already have the training data for

agentsdair-ai--x

Can You Trust the Confidence? ConfBench for Vision-Language Models on Document Extraction

model-releasesarxiv-cs-cl

arXiv:2608.01792v1 Announce Type: cross Abstract: Intelligent document processing (IDP) with vision-language models (VLMs) hinges on confidence scores trustworthy enough to route extractions between a

Cardiovascular Digital Twins from Physics Based to Data Driven Approaches

arXiv:2608.02135v1 Announce Type: cross Abstract: Cardiovascular digital twins aim to create patient-specific computational models that evolve with clinical data to support diagnosis, prognosis, and t

Climate-Dyna Deep Hedging for XVAs: Model-Based Reinforcement Learning, Residual Climate HVA, and Hedge-Instrument Discovery

arXiv:2608.01208v1 Announce Type: cross Abstract: For a trading desk, residual climate hedging valuation adjustment (HVA) is the climate cost left after its inherited hedge and any admissible overlay

CoNav-UAV: Cooperative Dual-Altitude Aerial Navigation via Stackelberg Learning

model-releasesarxiv-cs-ro

arXiv:2608.01802v1 Announce Type: cross Abstract: Target-oriented vision-and-language navigation (VLN) on aerial platforms is attracting growing attention for missions such as disaster rescue, infrast

Conformalized Large Language Models under Configuration Shift

arXiv:2608.01460v1 Announce Type: new Abstract: Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs)

Constrained Co-Design for Photonic Bayesian Neural Networks

arXiv:2608.02229v1 Announce Type: new Abstract: Classical neural networks frequently produce overconfident predictions on ambiguous or out-of-distribution (OOD) data, a liability that grows with each

safetyarxiv-cs-lg

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

model-releasesarxiv-cs-cl

arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whe

D^2-4DGS: Dual-Depth Guided Sparse-Camera 4D Gaussian Splatting

arXiv:2608.01588v1 Announce Type: new Abstract: Dynamic 4D Gaussian Splatting has emerged as an efficient representation for dynamic novel view synthesis through explicit scene modeling and real-time

researcharxiv-cs-cv

Development and Validation of a Dynamic Kidney Failure Prediction Model based on Deep Learning: A Real-World Study with External Validation

arXiv:2501.16388v3 Announce Type: replace Abstract: Background: Chronic kidney disease (CKD), a progressive disease with high morbidity and mortality, has become a significant global public health pro

DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation

arXiv:2608.01343v1 Announce Type: new Abstract: The emergence of transformer-based deep learning models has brought unprecedented performance across various domains, particularly in natural language p

researcharxiv-cs-cv

DF^3: World Modeling via Decoder-Free Feature Forecasting in Autonomous Navigation

arXiv:2608.02428v1 Announce Type: new Abstract: Forecasting future states from video sequences is a critical challenge for autonomous robotic systems and a fundamental objective of world modeling. Pri

agentsarxiv-cs-cv

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

Douyin Multimodal Embedding Model Technical Report

arXiv:2608.02148v1 Announce Type: cross Abstract: Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search

applicationsarxiv-cs-cl

DriveCode: Domain Specific Numerical Encoding for LLM-Based Autonomous Driving

arXiv:2603.00919v3 Announce Type: replace Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical rea

agentsarxiv-cs-cv

DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments

arXiv:2608.00402v1 Announce Type: new Abstract: Estimated Time of Arrival (ETA) prediction is a core component of intelligent transportation systems. As traffic congestion patterns become increasingly

EEG-FM-Compass: Progress, Benchmarking, and Future Directions for EEG Foundation Models

arXiv:2601.17883v3 Announce Type: replace-cross Abstract: Electroencephalography (EEG) foundation models (FMs) have recently emerged as a promising paradigm for brain-computer interfaces, aiming to le

Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs

model-releasesarxiv-cs-lg

arXiv:2511.00382v2 Announce Type: replace-cross Abstract: Organizations increasingly adapt Large Language Models (LLMs) from public repositories such as HuggingFace to downstream tasks. Prior work sho

Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data

arXiv:2608.02580v1 Announce Type: new Abstract: Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich

researcharxiv-cs-ro

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey

arXiv:2510.01925v3 Announce Type: replace Abstract: Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune

researcharxiv-cs-cl

Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling

arXiv:2608.01572v1 Announce Type: new Abstract: Autonomous driving (AD) systems have advanced rapidly over the past decade; however, robust perception under adverse weather conditions remains a major

agentsarxiv-cs-cv

Ethyca launches Astralis to govern enterprise AI agents in real time

model-releasessiliconangle

Data privacy engineering company Ethyca Inc. today launched Astralis, a platform that governs how enterprise artificial intelligence models and agents use company data in real time. The company is pit

Evaluating Forecasting Techniques for Hardware Errors on a Large-scale HPC System

arXiv:2608.01648v1 Announce Type: new Abstract: Hardware error logs in high-performance computing (HPC) systems provide early signals of abnormal behavior, yet there remain challenges in effectively f

Event ActivityNet: A Large-Scale Simulated-Event Benchmark for Untrimmed Action Understanding

arXiv:2608.01948v1 Announce Type: new Abstract: Long-horizon event-based action understanding remains underexplored because existing datasets largely comprise short, trimmed clips, while collecting na

Explainable Hybrid Feature Selection for Intrusion Detection in Internet of Medical Things Environments

arXiv:2608.00869v1 Announce Type: cross Abstract: Internet of Medical Things (IoMT) networks are hard to protect: devices are heterogeneous, computing resources are scarce, and traffic must be analyze

FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting

model-releasesarxiv-cs-lg

arXiv:2608.01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institution

FeDepth: Federated Learning for Depth Estimation under Robot Heterogeneity

arXiv:2608.01129v1 Announce Type: cross Abstract: Although recent robot perception research emphasizes training on data from diverse environments to improve generalization, most existing methods still

researcharxiv-cs-cv

Local Ai

FlowPilot: Real-Time World-Action Modeling for Agile UAV Navigation

arXiv:2608.00635v1 Announce Type: new Abstract: We present FlowPilot, a compact world-action model for real-time onboard UAV navigation from depth. Unlike map-then-optimize pipelines that require loca

local-aiarxiv-cs-ro

Local Ai

FreqNav: Stage-Wise Frequency Routing for Object-Oriented Aerial Vision-Language Navigation

arXiv:2608.00970v1 Announce Type: new Abstract: Object-oriented aerial vision-and-language navigation (VLN) requires searching for a described target and landing on it precisely, under long-horizon an

local-aiarxiv-cs-ro

Future Mode Part 2: The foundation for securing agentic browsing

model-releasesgoogle-cloud-ai

Editor's Note: Our Future Mode series will give businesses insight into how Chrome Enterprise is approaching AI in the browser. Stay tuned for more blogs in this series.Future Mode Part 2: The foundat

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

safetyarxiv-cs-lg

GaussianSelector: Lightweight Human-Guided Object Selection in 3D Gaussian Splatting with Graph Optimization

arXiv:2608.01492v1 Announce Type: new Abstract: Selecting a complete 3D object from a reconstructed scene with minimal user effort is essential for practical scene editing and embodied interaction. Ex

applicationsarxiv-cs-cv

Tutorials

Gecko: Fast Private Inference via Secure Public Encoder Offloading

arXiv:2608.02378v1 Announce Type: new Abstract: Private inference protects both user inputs and server models during neural network inference, but existing solutions remain too slow for practical depl

tutorialsarxiv-cs-lg

Tutorials

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

tutorialsarxiv-cs-cv

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM

arXiv:2509.22910v2 Announce Type: replace Abstract: Given that Visual SLAM relies on appearance cues for localization and scene understanding, texture-less or visually degraded environments (e.g., pla

applicationsarxiv-cs-ro

Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI

model-releasesarxiv-cs-lg

arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

HorusEye: Language as Dynamic Attention for Emergency Visual Analysis

arXiv:2606.14741v2 Announce Type: replace Abstract: We introduce HorusEye, Language as Dynamic Attention for Emergency Visual Analysis. Our investigation followed five stages. The first one is benchma

How Cloudflare enforces engineering standards using AI

We created the Cloudflare Codex, a governed body of engineering standards that AI agents consume across the development lifecycle. By pairing structured RFCs with agentic reviews, teams automatically

agentscloudflare-ai

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

arXiv:2608.02110v1 Announce Type: new Abstract: Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustn

safetyarxiv-cs-cl

Implicit Neural Representations for Multimodal Longitudinal Image Imputation and Interpolation

arXiv:2608.02324v1 Announce Type: new Abstract: Longitudinal multiparametric MRI is central to follow-up imaging in oncology, yet real-world clinical data are characterised by missing sequences, heter

applicationsarxiv-cs-cv

Learned Digital Over-the-Air Computing for Federated Edge Learning

arXiv:2509.16577v2 Announce Type: replace Abstract: Over-the-air (OTA) aggregation enables federated edge learning (FEEL) by exploiting the superposition property of the wireless channel to merge comm

Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control

arXiv:2608.00908v1 Announce Type: cross Abstract: Modern network policy control maps intent to sequential placement-control decisions. Bellman-style policy optimization primarily asks which action to

safetyarxiv-cs-lg

Learning the Pareto Frontier of Predictive Models under Distribution Shift

arXiv:2608.00632v1 Announce Type: new Abstract: Modern machine learning pipelines increasingly rely on reusing pretrained and foundation models across downstream tasks. These pretrained models can dif

Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention

arXiv:2602.04789v4 Announce Type: replace Abstract: Advanced autoregressive (AR) video generation models have improved visual fidelity and interactivity, but the quadratic complexity of attention rema

LLM-OSDA: An Optimal-Stopping Dynamic Auction for Native Advertising in Multi-Turn LLM Conversations

arXiv:2608.00123v1 Announce Type: new Abstract: LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within

safetyarxiv-cs-cl