Search: “models”

How Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification

arXiv:2608.03511v1 Announce Type: cross Abstract: Active learning (AL) promises to reduce the cost of medical imaging projects by lowering the number of clinical labels required. However, practical de

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Research

HyperbolicDiffusion: Sharp & Scalable Tiled Generation on the Hyperbolic Plane

DGX agent

arXiv:2608.03422v1 Announce Type: new Abstract: Planar tiled diffusion denoises overlapping windows of one rectangular canvas. The hyperbolic plane has no such canvas, and its area grows exponentially

researcharxiv-cs-cv

5 Aug 2026

Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration

arXiv:2503.13077v2 Announce Type: replace Abstract: Multi-agent reinforcement learning has shown promise in learning cooperative behaviors in team-based environments. However, such methods often deman

agentsarxiv-cs-lg

Information-Geometric Forward Policy Training in GFlowNets

arXiv:2608.03967v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) have emerged as a flexible framework for amortised inference over discrete and mixed discrete-continuous objects,

local-aiarxiv-cs-lg

Language-Specialized Multi-Teacher On-Policy Distillation for Multilingual LLM-Based ASR

arXiv:2608.03610v1 Announce Type: new Abstract: Modern LLM-based ASR systems have established multilingual capability as a standard feature, leveraging large-scale multilingual corpora and LLMs' cross

safetyarxiv-cs-cl

Learning Biomechanically Plausible Human Motion from Sparse Radar Point Clouds

arXiv:2608.03637v1 Announce Type: new Abstract: Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We add

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents

arXiv:2608.03606v1 Announce Type: new Abstract: Clinical development is sequential decision-making under uncertainty, where a sponsor must plan a portfolio of experiments from heterogeneous evidence.

LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation

arXiv:2608.03382v1 Announce Type: cross Abstract: Multi-armed bandit algorithms, especially Thompson sampling, are widely used in online recommendation. Despite their ability to adapt from online feed

safetyarxiv-cs-lg

MAFIA: Query-Only Memory Attacks via Probing and Factual Injection against Audited LLM Agents

arXiv:2608.03844v1 Announce Type: new Abstract: Memory-augmented LLM agents rely on rich context for long-horizon reasoning and acting, yet their memory modules expose a persistent attack surface for

agentsarxiv-cs-ai

Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation

arXiv:2403.16178v2 Announce Type: replace-cross Abstract: For effective human-agent teaming, robots and other artificial intelligence (AI) agents must infer their human partner's abilities and behavio

agentsarxiv-cs-ai

On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

arXiv:2608.02671v1 Announce Type: cross Abstract: Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a comp

Optimal Liability Design for Medical AI

arXiv:2608.03114v1 Announce Type: cross Abstract: Artificial intelligence (AI) is increasingly integrated into medical decision-making, yet its liability implications remain complex, particularly when

OR-Agent: Bridging Evolutionary Search and Structured Research for Automated Algorithm Discovery

arXiv:2602.13769v3 Announce Type: replace Abstract: Automating heuristic design in complex, experiment-driven domains requires more than iterative mutation of solution algorithms. Current LLM-based ev

agentsarxiv-cs-ai

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation

arXiv:2608.03991v1 Announce Type: new Abstract: Training-free open-vocabulary semantic segmentation (OVSS) partitions an image into semantically distinct regions based on arbitrary text descriptions,

safetyarxiv-cs-cv

Applications

PLS-Calib: A Partial Least Squares Framework for Event Camera and Odometry Calibration under Ground Motion Constraints

arXiv:2608.03296v1 Announce Type: cross Abstract: Accurate extrinsic rotation calibration between sensors is fundamental to the performance of robotic perception systems. However, most existing calibr

applicationsarxiv-cs-cv

POEM: Phase-Aware SO(2) Feature Rotation for Time Series Forecasting Under Periodicity Drift

arXiv:2608.03630v1 Announce Type: new Abstract: Deep learning has advanced time series forecasting, but periodicity drift, in which cycle timing and phase vary over time, remains a challenging problem

PolyLayout: Multi-room Manhattan Layout Estimation

arXiv:2608.03323v1 Announce Type: new Abstract: Estimating room layouts from multi-view imagery is a core task for indoor scene understanding. Existing methods are typically limited either by poor gen

Predictive Set Theory: A Generative Framework for Cognitive Architecture with Operationalized Core Mechanisms

arXiv:2608.02704v1 Announce Type: new Abstract: Predictive processing theories portray the brain as a hierarchical prediction engine that minimizes prediction error, yet they lack operational definiti

PULSE: An Executable Contract Language for Spatiotemporal Knowledge Graph Engineering

arXiv:2608.02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose co

ReCamDriving: LiDAR-Free Camera-Controlled Video Synthesis for Novel Trajectories

arXiv:2512.03621v3 Announce Type: replace Abstract: Synthesizing multi-pass videos is important for autonomous driving. While current repair-based methods often struggle with out-of-distribution artif

agentsarxiv-cs-cv

Risk Occupancy: A New and Efficient Paradigm through Vehicle-Road-Cloud Collaboration

arXiv:2408.07367v3 Announce Type: replace Abstract: This paper proposes a novel 4D risk occupancy (RiskOcc) perception paradigm under the Vehicle-Road-Cloud integrated architecture, which unifies obje

local-aiarxiv-cs-ro

Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms

arXiv:2608.02656v1 Announce Type: cross Abstract: The Secured data safe guard transaction with multi-tenant environments run on private-protected authenticate platforms runs by secured handed environm

Self-Supervised Representation-Guided Generative Dataset Distillation

arXiv:2608.03218v1 Announce Type: cross Abstract: Dataset distillation compresses a large training set into a compact synthetic set while retaining its downstream utility. Most existing methods target

Self-Supervised Uncalibrated Multi-View Video Anonymization in the Operating Room

arXiv:2602.02850v3 Announce Type: replace Abstract: Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effective anonymization relies on the exhaustive locali

local-aiarxiv-cs-cv

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning

arXiv:2608.03378v1 Announce Type: cross Abstract: The development and testing of advanced aerial robots require experiments in controlled environments with tailored airflow profiles. This paper presen

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

arXiv:2608.03250v1 Announce Type: cross Abstract: The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting i

Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory

arXiv:2608.03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set o

SpreadMark: Robust Image Watermarking via Spread-Spectrum Embedding

arXiv:2608.03165v1 Announce Type: cross Abstract: Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortio

SRAP: SVD-Refined Adversarial Perturbations for Imperceptible Face-Swap Defense

arXiv:2608.03395v1 Announce Type: new Abstract: Deepfake technologies pose increasing threats to facial privacy and identity security, motivating proactive defenses that protect facial images before m

Standalone DINOv3 for Training-Free Open-Vocabulary Semantic Segmentation in Remote Sensing

arXiv:2608.03023v1 Announce Type: cross Abstract: Remote sensing semantic segmentation is hindered by costly pixel-level annotations, motivating training-free open-vocabulary methods. Recently, the re

Stochastic Saddle Avoidance Beyond Unit Excitation and Smoothness: A Pathwise Lyapunov-Perron Framework

arXiv:2608.03001v1 Announce Type: cross Abstract: Unit excitation (UE) is a common assumption in stochastic saddle avoidance: the stochastic error must have a uniformly positive component along every

Applications

SynEnergy: Anomaly Semantic-Guided Diffusion for Synthetic Energy Data Generation

arXiv:2608.03087v1 Announce Type: cross Abstract: Fine-grained energy consumption data are essential for applications such as demand forecasting, demand response planning, and grid reliability assessm

applicationsarxiv-cs-ai

TabletCraft: Bridging a 4,000-Year Cultural Gap with Bidirectional Akkadian NMT and Cuneiform Rendering

arXiv:2608.02609v1 Announce Type: new Abstract: Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, le

researcharxiv-cs-cl

Target-Aligned Fusion for Decision-Sequence Learning under Dynamics Shift

arXiv:2511.09173v3 Announce Type: replace-cross Abstract: External trajectories can improve offline decision-sequence learning, but dynamics shift may make some source subsequences inconsistent with t

local-aiarxiv-cs-ai

TDVR: Joint Text Disambiguation and Viewpoint Reasoning for Zero-Shot 3D Visual Grounding

arXiv:2608.03763v1 Announce Type: new Abstract: Zero-shot 3D visual grounding aims to localize specific objects based on textual descriptions and 3D visual input. However, the effectiveness of existin

local-aiarxiv-cs-cv

Tired Actor: Fatigue-Informed Character Control

arXiv:2608.03528v1 Announce Type: new Abstract: Replicating human behavior with physics simulation has been a long-expected goal in character animation. Existing efforts have achieved impressive perfo

safetyarxiv-cs-ro

Two-Way Garment Transfer: Unified Diffusion Framework for Dressing and Undressing Synthesis

arXiv:2508.04551v2 Announce Type: replace Abstract: While recent advances in virtual try-on (VTON) have achieved realistic garment transfer to human subjects, its inverse task, virtual try-off (VTOFF)

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors

arXiv:2608.03008v1 Announce Type: cross Abstract: As generated videos become increasingly realistic, reliable video forgery detection is increasingly important. Existing studies typically optimize and

Virtual Patients, Real Gains: Digital Twin-Based Simulated CT for Multitask Lung Nodule Analysis

arXiv:2502.21187v4 Announce Type: replace Abstract: AI-based lung cancer screening is constrained by scarce, annotated CT data, particularly for rare nodule presentations. We investigate whether physi

When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking

arXiv:2608.03902v1 Announce Type: new Abstract: Resource constraints on UAV platforms have driven a paradigm shift in aerial tracking, from pursuing performance toward balancing accuracy with efficien

local-aiarxiv-cs-ai

When Should Graph Attention Be Sparse? Learning a Per-Edge Tsallis Index

arXiv:2608.02938v1 Announce Type: cross Abstract: Graph attention normalizes neighborhood scores with softmax, the maximum-entropy choice under Shannon statistics. But homophilic and heterophilic grap

Where Reasoning Diverges: Localized Multi-Agent Debate for Multi-Hop Question Answering

arXiv:2608.01463v2 Announce Type: replace Abstract: Multi-agent debate commonly exchanges complete rationales even when disagreements concern only a few intermediate claims. We introduce Localized Mul

local-aiarxiv-cs-ai

A drone that learns to efficiently find non-uniformly distributed objects in agricultural fields: from simulation to the real world

arXiv:2505.09278v2 Announce Type: replace Abstract: Drones are promising for data collection in precision agriculture but are limited by battery capacity. Drone paths are usually planned using full co

agentsarxiv-cs-ro

A False Average: Chain-of-Thought Monitors Collapse Where They Are the Only Defense

arXiv:2608.00583v1 Announce Type: cross Abstract: Chain-of-thought (CoT) monitoring is meant to catch the reward hacks that look clean in the actions and betray themselves only in the reasoning. We sh

agentsarxiv-cs-cl

A Physics-Chemistry-Informed Neural Network (PCINN) for Real-Time Spatial-ALD Coverage Prediction and Reliable Kinetics Inversion

arXiv:2608.00212v1 Announce Type: new Abstract: Spatial atomic layer deposition (SALD) is a leading atmospheric-pressure, high-throughput route to industrial ALD, but design and control are limited by

AdaThinkV: Adaptive Thinking for Token-Efficient Video Reasoning

arXiv:2608.01980v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning can improve performance on difficult video questions but often wastes decoding tokens on simple ones. We study whether

safetyarxiv-cs-cv

An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition

arXiv:2608.00796v1 Announce Type: cross Abstract: Automatic RF modulation recognition is of critical importance in spectrum monitoring, electronic warfare, and cognitive radio applications, where low

AOS: Adaptive Optimizer Switching via Training-State Signals for Faster Convergence and Better Generalization

arXiv:2608.01997v1 Announce Type: new Abstract: Single-optimizer training is a poor fit for the distinct phases of deep network optimization: adaptive methods handle noisy early gradients well but ove