Search: “deployment”

STREAM-VAE: Dual-Path Routing for Slow and Fast Dynamics in Vehicle Telemetry Anomaly Detection

model-releasesarxiv-cs-ai

arXiv:2511.15339v3 Announce Type: replace-cross Abstract: Automotive telemetry data exhibits slow drifts and fast spikes, often within the same sequence, making reliable anomaly detection challenging.

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Stylometric Defenses Against Author Impersonation in Software Repositories

DGX agent

arXiv:2608.02695v1 Announce Type: cross Abstract: Software supply-chain attacks increasingly exploit an identity gap where compromised maintainer accounts authorize malicious changes. This work evalua

applicationsarxiv-cs-lg

5 Aug 2026

Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores

arXiv:2608.02985v1 Announce Type: cross Abstract: The standard check for contamination in LLM backtests is simple: compare scores before and after the training cutoff. We show this check is uninformat

researcharxiv-cs-cl

Test-Time Scaling for Safe Text-Guided Image Generation via Intermediate Clean Estimates

arXiv:2608.03284v1 Announce Type: cross Abstract: Ensuring safety and policy compliance in text-to-image diffusion models remains a critical challenge, as benign or adversarial prompts can often elici

safetyarxiv-cs-ai

The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems

arXiv:2608.03214v1 Announce Type: new Abstract: Large language models have transformed artificial intelligence from isolated prediction services into components of long-running, distributed systems th

safetyarxiv-cs-ai

TQLite: Multi-LLM Jury Guided Distillation for Real-time MQM Translation Quality Evaluation

arXiv:2608.02975v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive performance in MQM-based translation quality (TQ) evaluation, and recent advances in large r

applicationsarxiv-cs-ai

UniEvo-RS: Omni-Prompt Unified Remote Sensing Segmentation with Representative Exemplar-Driven Prototype Evolution

arXiv:2608.03911v1 Announce Type: new Abstract: Prompt-driven vision-language models (VLMs) hold immense promise for accelerating dense remote sensing (RS) annotation, but static models suffer from se

When Policies Change Probabilities: Modular Decision-Making for LLM Code Review

arXiv:2608.02677v1 Announce Type: cross Abstract: LLM code reviewers often estimate patch risk and make approval decisions in one prompt. A probability should depend on evidence; costs should determin

safetyarxiv-cs-ai

A 2-Block Architecture for Real-Time EEG Gait Decoding: A Pilot Study

arXiv:2608.02083v1 Announce Type: new Abstract: Closed-loop lower-limb exoskeleton control via Electroencephalography (EEG) remains limited by motion artifacts, low signal-to-noise ratio, and binary g

A Large-Scale Multi-Dimensional Empirical Study of LLMs for Conversation Summarization

model-releasesarxiv-cs-cl

arXiv:2606.15974v2 Announce Type: replace Abstract: Despite the significant advancement of LLMs in conversation summarization, their evaluation remains limited by insufficient scenarios, input lengths

A Multi-Objective AutoML-based Efficient Intrusion Detection System for EV Charging Networks

arXiv:2608.02274v1 Announce Type: cross Abstract: Electric Vehicle Charging Systems (EVCSs) are increasingly connected with Internet of Things (IoT) devices, which improves charging intelligence but a

Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning

arXiv:2608.00301v1 Announce Type: cross Abstract: Error-penalized scoring rules (+1 for a correct answer, -lambda for a wrong one, 0 for abstaining) are increasingly prescribed against hallucination:

agentsarxiv-cs-cl

Advancing Relevance Measurement with Vision-Language Models for Web-Scale Search

arXiv:2608.02446v1 Announce Type: cross Abstract: Relevance evaluation plays a crucial role in personalized search systems, serving as a guardrail alongside user engagement metrics to ensure that sear

ARMOR: Robust Reinforcement Learning-based Control for UAVs under Physical Attacks

arXiv:2506.22423v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles (UAVs) depend on onboard sensors for perception, navigation, and control. However, these sensors are susceptible to physica

Artificial Intelligence for the Characterization of Particles and Fibers by Optical Microscopy

arXiv:2608.00361v1 Announce Type: new Abstract: Optical microscopy of particle and fiber dispersions involves interpreting subtle visual cues influenced by specimen morphology, chemical composition, m

Automated ECG Interval Measurement and Wave Delineation Using Fast Fourier Convolution ResNet

arXiv:2608.00058v1 Announce Type: cross Abstract: Accurate measurement of ECG intervals, including PR, QRS duration, and QT/QTc, is central to cardiac diagnosis, yet the published ECG delineation lite

Belief-Space Perception Routing under Coupled Sensor Faults and Compute Contention

model-releasesarxiv-cs-cv

arXiv:2608.00322v1 Announce Type: cross Abstract: A robot that has to see and react on a fixed clock runs into two problems at once. Its cameras degrade in rain, mud, fog, and darkness. And the single

Hardware

Bole: Efficient Tree Speculation for Hybrid-Attention Language Models

arXiv:2608.01651v1 Announce Type: cross Abstract: Hybrid-attention large language models combine full attention with recurrent linear attention to reduce long-context inference costs, yet their autore

hardwarearxiv-cs-cl

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

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

model-releasesarxiv-cs-lg

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

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

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

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

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

model-releasesarxiv-cs-cv

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

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

model-releasesarxiv-cs-cv

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

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

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