Search: “applications”

Beyond Binary Priorities: Multi-Tier SLA Scheduling for Large Language Model Serving

arXiv:2608.16336v1 Announce Type: cross Abstract: Modern LLM serving deployments must simultaneously satisfy heterogeneous service-level objectives (SLOs) across a diverse population of user tiers, ra

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Research

Binarized High-Efficiency RAW Video Restoration and Beyond

DGX agent

arXiv:2608.16756v1 Announce Type: new Abstract: RAW video restoration is fundamental to high-quality low-level perception and serves as the basis for a wide range of downstream vision applications. Wh

researcharxiv-cs-cv

18 Aug 2026

Bit-Level Triangular Content-Aware Permutation for Fragile Image Watermarking: Zero False Positive Rate, Single-Bit Sensitivity, and Arbitrary Dimension Support

arXiv:2608.14800v1 Announce Type: cross Abstract: With the growth of digital document exchange, protecting image integrity against attacks such as Vector Quantization (VQ) and collage has become criti

Can Unsupervised Methods Outperform Supervised Deep Learning When Ground Truth Is Sparse? A Case Study of Bronchovascular Bundle Segmentation in Low-Dose CT

arXiv:2608.16855v1 Announce Type: new Abstract: Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an ear

DA-RAC: Distance-Aware Calibration of LLM Judges for Trustworthy AI Auditing

arXiv:2608.14950v1 Announce Type: new Abstract: Generative AI systems are increasingly producing real-world artifacts, however their efficacy and validity are often evaluated via context-free LLM-scor

Decomposing Staleness in Recommender Systems: A Dual-Filter Framework for Supersession and Decay

arXiv:2608.15780v1 Announce Type: cross Abstract: Stale recommendations are a pervasive challenge and a leading source of user complaints on large-scale content platforms. Items lose relevance through

Demand-Driven Vertiport Siting and Discrete-Event Fleet Simulation for On-Demand Urban Air Mobility Network Design

arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and d

DiSA-IQL: Offline Reinforcement Learning for Robust Soft Robot Control under Distribution Shifts

arXiv:2510.00358v2 Announce Type: replace-cross Abstract: Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly n

Distinguishing AI-Generated Music from Edited Audio as a Hard-Negative Robustness Task

arXiv:2608.14916v1 Announce Type: cross Abstract: AI-generated music detectors are commonly evaluated against original songs, but real-world uploads are often remixed, re-encoded, pitch-shifted, or ot

Do Assessment Instruments Measure the Same Thing for Humans and LLMs? A Latent Structure Analysis

arXiv:2608.15630v1 Announce Type: cross Abstract: The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A c

DPNet: Efficient Dead-End Prediction and Avoidance for Vision-Based UAV Navigation

arXiv:2608.16640v1 Announce Type: new Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) often suffer from navigation failures in dead ends due to limited sensing accuracy and range. To address th

Efficient Coreset Selection via K-Nearest Neighbor Graphs

arXiv:2608.16270v1 Announce Type: new Abstract: Coreset selection reduces the cost of model training by replacing a large training set with a small representative subset. Existing gradient-approximati

EMS Coreset: An Efficient Expectation-Maximization Algorithm for Sinkhorn Coreset

arXiv:2608.16101v1 Announce Type: cross Abstract: Coresets distill large datasets into small, representative subsets for efficient downstream learning. Yet Optimal Transport (OT)-based selection typic

Enhancing Differentially Private Linear Regression via Public Second-Moment

arXiv:2508.18037v2 Announce Type: replace Abstract: Leveraging information from public data has become increasingly crucial in enhancing the utility of differentially private (DP) methods. Traditional

Research

Evaluating the trustworthiness of the Frechet Inception Distance with stochastic embedding representations

arXiv:2601.21979v2 Announce Type: replace Abstract: Feature embeddings acquired from pretrained models are widely used in medical applications of deep learning to assess the characteristics of dataset

researcharxiv-cs-lg

Faster, Cheaper, More Accurate: Specialised Knowledge Tracing Models Outperform LLMs

arXiv:2603.02830v2 Announce Type: replace-cross Abstract: Predicting future student responses to questions is particularly valuable for educational learning platforms where it enables effective interv

Federated Self-Supervised Modulation Classification under Non-IID and Imbalanced Data

arXiv:2510.04927v2 Announce Type: replace-cross Abstract: Automatic modulation classification (AMC) is a core enabler of cognitive wireless systems, providing spectrum awareness and supporting adaptiv

FollowUpBot: An LLM-Based Conversational Robot for Automatic Postoperative Follow-up

arXiv:2507.15502v1 Announce Type: cross Abstract: Postoperative follow-up plays a crucial role in monitoring recovery and identifying complications. However, traditional approaches, typically involvin

GAINS: Leveraging Inconsistent Human Intervention Signals in Reinforcement Learning

arXiv:2608.15707v1 Announce Type: new Abstract: Correcting robot manipulation policies through human intervention holds great promise for real-world deployment, yet human operators are inherently impe

GOD: Enhancing Generalization via Deep Grafting for Sequential Recommendation

arXiv:2608.16073v1 Announce Type: cross Abstract: Sequential recommenders often struggle with sparse and noisy histories, limiting generalization to unseen interactions. Knowledge distillation mitigat

Grounding Healthcare LLMs in a Causal Knowledge Graph: Framework, Metrics, and a Cardiovascular Pilot

arXiv:2608.15382v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for healthcare decision support, but their evaluations still reward single-answer accuracy rather

GUIDER: Evaluating Goal-Free Human Intent Inference for Teleoperated Manipulation on Real-Robot Data

arXiv:2608.15446v1 Announce Type: new Abstract: This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global Us

Handover Analysis for Vehicular Communication with Explainability on the Fly

arXiv:2608.14820v1 Announce Type: cross Abstract: Handover (HO) management in vehicular networks requires fast and reliable decision-making under highly dynamic conditions. While machine learning (ML)

HaReCAP: Habitual-action Grounding for Recursive Large Language Model Agents

arXiv:2608.16447v1 Announce Type: new Abstract: Long-horizon embodied tasks require LLM agents to iteratively decompose high-level goals, revise plans in response to environmental feedback, and ground

LUNG-KGMM: Knowledge-Guided Multimodal Learning for Lung Cancer Incidence Prediction

arXiv:2608.14657v1 Announce Type: cross Abstract: Early identification of lung cancer risk is critical for timely intervention, yet existing prediction models are limited by their reliance on single d

Maintaining IoT Device Identification under Concept Drift via Budget-Aware Traffic Labeling

arXiv:2608.15465v1 Announce Type: cross Abstract: Identification of IoT device types from passive traffic is increasingly used for security management in enterprise and ISP networks. However, the perf

ML-AutoResearch: Training Machine Learning Research Agents with Automatically Generated Environments

arXiv:2603.17216v2 Announce Type: replace Abstract: With the advent of AI agents, automated scientific discovery is becoming an increasingly plausible goal. However, training agents to autonomously ex

Local Ai

Offline Ambient-Controlled Latent Diffusion: Architecture, Telemetry, and On-Device Evaluation

arXiv:2608.14677v1 Announce Type: cross Abstract: Most mobile image-generation applications are thin clients over cloud services, leaving outputs hard to audit. We present an Android latent-diffusion

local-aiarxiv-cs-ai

PandasCorpus: A Resource of Real-World Pandas Workflows and Usage Patterns

arXiv:2608.14742v1 Announce Type: cross Abstract: Pandas has emerged as the de facto library for data processing and machine learning, widely used for tasks, such as data loading, transformation, and

PCT-Prompt: A Prompt-Guided Transformer Framework for Dense Prediction Tasks in Point Clouds

arXiv:2608.16225v1 Announce Type: new Abstract: Standard Transformers have proven effective in point cloud object classification, but their performance in dense prediction tasks within complex scenes

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as

PhyxMamba: Chaotic System Reconstruction from Short Context Observations with Generative State-Space Models

arXiv:2505.23863v3 Announce Type: replace-cross Abstract: Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dyna

Plausible but Not Valid: A Psychometric Audit of LLMs as Synthetic Survey Respondents

arXiv:2608.14606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the

PolyDebate: A Game-Orchestrated Multimodal System for Debate Skills Practice and Evaluation

arXiv:2608.16276v1 Announce Type: cross Abstract: Debate is a structured form of persuasive communication that trains argument construction, rebuttal, oral delivery, and audience awareness. These skil

Pricing the Risk of Runtime Compression: Anytime-Valid Admission and a Served-Output Law for Compressed Serving State

arXiv:2608.15810v1 Announce Type: new Abstract: Runtime compression of serving state trades quality for capacity with no priced guarantee: systems adapt precision on load signals with no soundness sta

Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy

arXiv:2509.10691v3 Announce Type: replace-cross Abstract: Decentralized federated learning enables collaborative model training without a central server, but shared model updates can still leak sensit

RAGas: Retrieval-Augmented Gas Optimization for Smart Contracts with Continuous Knowledge Integration

arXiv:2608.15857v1 Announce Type: new Abstract: Ethereum is now integral to mission-critical sectors, including finance, healthcare, and supply chain management. Execution fees, commonly referred to a

Real-time Estimator of Actuator Control and Health (REACH) on an Eel-Inspired Soft Robot

arXiv:2608.14865v1 Announce Type: new Abstract: An actuator health estimation algorithm for a soft swimming robot that can perform anguilliform swimming is developed. Due to harsh operational environm

Revisiting Open-Loop Execution in Robotics: Toward Reactive, Higher-Performing Policies

arXiv:2608.15938v1 Announce Type: new Abstract: Action chunking --- the practice of predicting a sequence of actions and executing a prefix open-loop --- has emerged as a key enabler of recent progres

Self-Supervised Topologically Invariant Manifold Learning for Railway Image Quality Assessment

arXiv:2608.15217v1 Announce Type: new Abstract: Existing blind image quality assessment (BIQA) methods typically rely on synthetic distortions and subjective annotations, limiting generalization in re

Synchronized Logit Steering: Real-world Steganography

arXiv:2608.14697v1 Announce Type: new Abstract: Steganography in large language models offers a way to embed hidden messages within natural-sounding text. Existing token and logit-level methods typica

Take it Personally: The Limits of General SSL Representations for Real-Life PPG Emotion Detection

arXiv:2608.14675v1 Announce Type: cross Abstract: While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethys

Time as Structure: Temporal Dependency Graphs for Verifiable Deadline Computation over Legal Documents

arXiv:2608.15270v1 Announce Type: new Abstract: Miss a filing deadline by one day and the claim is barred, however strong the case. Computing that deadline is rarely simple: the period runs from a tri

Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1,Hz Operational Data, CCGS extit{Sir Wilfrid Laurier}

arXiv:2608.16833v1 Announce Type: new Abstract: Ship fuel consumption (SFC) prediction supports vessel operation optimisation, emissions estimation, and decision support systems (DSS) for sustainable

Model Releases

Toward Better Assessment of LLMs' Performance in Clinical Error Detection

model-releasesarxiv-cs-ai

arXiv:2608.16643v1 Announce Type: cross Abstract: Automated detection of errors in clinical documentation is a promising application of large language models (LLMs), yet decisions to deploy such model

Training-Free Reconstruction-Based AI-Generated Image Detectors Are Inherently Vulnerable to Adversarial Examples

arXiv:2608.16646v1 Announce Type: new Abstract: The impressive visual quality and ubiquity of AI-generated images call for reliable and robust detection methods. Reconstruction-based detectors have em

Research

TransfHAR: Self-Supervised Wrist Representations for On-Demand Activity Recognition

arXiv:2608.15861v1 Announce Type: new Abstract: Fine-grained wrist activity recognition can support applications such as procedural step guidance and context-aware assistance, yet acquiring labeled da

researcharxiv-cs-lg

Underwater Color Restoration with Vanishing Uncertainty

arXiv:2608.15598v1 Announce Type: cross Abstract: Underwater color restoration promises to unlock color as a reliable signal for aquatic sciences, but achieving this with scientific confidence remains