Search: “models”

Offline-Online Reinforcement Learning for Linear Mixture MDPs

arXiv:2604.11994v1 Announce Type: new Abstract: We study offline-online reinforcement learning in linear mixture Markov decision processes (MDPs) under environment shift. In the offline phase, data ar

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OmniHands: Towards Robust 4D Hand Mesh Recovery via A Versatile Transformer

DGX agent

arXiv:2405.20330v4 Announce Type: replace-cross Abstract: In this paper, we introduce OmniHands, a universal approach to recovering interactive hand meshes and their relative movement from monocular o

model-releasesarxiv-cs-ai

15 Apr 2026

Local Ai

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning

arXiv:2604.12100v1 Announce Type: new Abstract: Whole-slide image (WSI) classification in computational pathology is commonly formulated as slide-level Multiple Instance Learning (MIL) with a single g

local-aiarxiv-cs-cv

Physically Accurate Rigid-Body Dynamics in Particle-Based Simulation

model-releasesarxiv-cs-ro

arXiv:2603.14634v3 Announce Type: replace Abstract: Robotics demands simulation that can reason about the diversity of real-world physical interactions, from rigid to deformable objects and fluids. Cu

PrivEraserVerify: Efficient, Private, and Verifiable Federated Unlearning

arXiv:2604.12348v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training without sharing raw data, offering a promising path toward privacy preserving artificial in

researcharxiv-cs-lg

QMC-Net: Data-Aware Quantum Representations for Remote Sensing Image Classification

arXiv:2604.11817v1 Announce Type: cross Abstract: Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imager

researcharxiv-cs-cv

Reasoning about Intent for Ambiguous Requests

arXiv:2511.10453v3 Announce Type: replace-cross Abstract: Large language models often respond to ambiguous requests by implicitly committing to one interpretation, frustrating users and creating safet

Representing expertise accelerates learning from pedagogical interaction data

arXiv:2604.12195v1 Announce Type: new Abstract: Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals

Scale-aware Message Passing For Graph Node Classification

arXiv:2411.19392v3 Announce Type: replace Abstract: Most Graph Neural Networks (GNNs) operate at the first-order scale, even though multi-scale representations are known to be crucial in domains such

Scaling In-Context Segmentation with Hierarchical Supervision

arXiv:2604.12752v1 Announce Type: new Abstract: In-context learning (ICL) enables medical image segmentation models to adapt to new anatomical structures from limited examples, reducing the clinical a

researcharxiv-cs-cv

SIR-Bench: Evaluating Investigation Depth in Security Incident Response Agents

arXiv:2604.12040v1 Announce Type: cross Abstract: We present SIR-Bench, a benchmark of 794 test cases for evaluating autonomous security incident response agents that distinguishes genuine forensic in

Sparse Growing Transformer: Training-Time Sparse Depth Allocation via Progressive Attention Looping

model-releasesarxiv-cs-cl

arXiv:2603.23998v2 Announce Type: replace Abstract: Existing approaches to increasing the effective depth of Transformers predominantly rely on parameter reuse, extending computation through recursive

Style-Decoupled Adaptive Routing Network for Underwater Image Enhancement

arXiv:2604.12257v1 Announce Type: new Abstract: Underwater Image Enhancement (UIE) is essential for robust visual perception in marine applications. However, existing methods predominantly rely on uni

SynthPix: A lightspeed PIV image generator

arXiv:2512.09664v2 Announce Type: replace-cross Abstract: We describe SynthPix, a synthetic image generator for Particle Image Velocimetry (PIV) with a focus on performance and parallelism on accelera

TimeMark: A Trustworthy Time Watermarking Framework for Exact Generation-Time Recovery from AIGC

arXiv:2604.12216v1 Announce Type: cross Abstract: The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes. Watermarkin

Transferable Expertise for Autonomous Agents via Real-World Case-Based Learning

arXiv:2604.12717v1 Announce Type: new Abstract: LLM-based autonomous agents perform well on general reasoning tasks but still struggle to reliably use task structure, key constraints, and prior experi

TRUST Agents: A Collaborative Multi-Agent Framework for Fake News Detection, Explainable Verification, and Logic-Aware Claim Reasoning

arXiv:2604.12184v1 Announce Type: new Abstract: TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a

UCS: Estimating Unseen Coverage for Improved In-Context Learning

arXiv:2604.12015v1 Announce Type: cross Abstract: In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heur

Understanding and Improving Continuous Adversarial Training for LLMs via In-context Learning Theory

arXiv:2604.12817v1 Announce Type: new Abstract: Adversarial training (AT) is an effective defense for large language models (LLMs) against jailbreak attacks, but performing AT on LLMs is costly. To im

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Local Ai

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving

arXiv:2604.12208v1 Announce Type: cross Abstract: Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental result

local-aiarxiv-cs-ai

When Does Data Augmentation Help? Evaluating LLM and Back-Translation Methods for Hausa and Fongbe NLP

arXiv:2604.12540v1 Announce Type: cross Abstract: Data scarcity limits NLP development for low-resource African languages. We evaluate two data augmentation methods -- LLM-based generation (Gemini 2.5

XRZero-G0: Pushing the Frontier of Dexterous Robotic Manipulation with Interfaces, Quality and Ratios

arXiv:2604.13001v1 Announce Type: new Abstract: The acquisition of high-quality, action-aligned demonstration data remains a fundamental bottleneck in scaling foundation models for dexterous robot man

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A Benchmark and Multi-Agent System for Instruction-driven Cinematic Video Compilation

arXiv:2604.10456v1 Announce Type: new Abstract: The surging demand for adapting long-form cinematic content into short videos has motivated the need for versatile automatic video compilation systems.

A Comparative Study of Modern Object Detectors for Robust Apple Detection in Orchard Imagery

arXiv:2604.09996v1 Announce Type: new Abstract: Accurate apple detection in orchard images is important for yield prediction, fruit counting, robotic harvesting, and crop monitoring. However, changing

A Comparative Theoretical Analysis of Entropy Control Methods in Reinforcement Learning

arXiv:2604.09676v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a key approach for enhancing reasoning in large language models (LLMs), yet scalable training is often hindered

Tutorials

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions

arXiv:2604.10328v1 Announce Type: cross Abstract: Accurate weather nowcasting remains one of the central challenges in atmospheric science, with critical implications for climate resilience, energy se

tutorialsarxiv-cs-ai

A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s

researcharxiv-cs-ai

A mathematical theory of evolution for self-designing AIs

arXiv:2604.05142v2 Announce Type: replace Abstract: As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, with the traits

Local Ai

A Modular Zero-Shot Pipeline for Accident Detection, Localization, and Classification in Traffic Surveillance Video

arXiv:2604.09685v1 Announce Type: new Abstract: We describe a zero-shot pipeline developed for the ACCIDENT @ CVPR 2026 challenge. The challenge requires predicting when, where, and what type of traff

local-aiarxiv-cs-cv

A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health

arXiv:2604.11125v1 Announce Type: new Abstract: India generates vast biomedical data through postgraduate research, government hospital services and audits, government schemes, private hospitals and t

A Ray Intersection Algorithm for Fast Growth Distance Computation Between Convex Sets

model-releasesarxiv-cs-ro

arXiv:2604.10058v1 Announce Type: new Abstract: In this paper, we discuss an efficient algorithm for computing the growth distance between two compact convex sets with representable support functions.

A Triadic Suffix Tokenization Scheme for Numerical Reasoning

arXiv:2604.11582v1 Announce Type: cross Abstract: Standard subword tokenization methods fragment numbers inconsistently, causing large language models (LLMs) to lose positional and decimal structure -

researcharxiv-cs-ai

AC-MIL: Weakly Supervised Atrial LGE-MRI Quality Assessment via Adversarial Concept Disentanglement

arXiv:2604.10303v1 Announce Type: new Abstract: High-quality Late Gadolinium Enhancement (LGE) MRI can be helpful for atrial fibrillation management, yet scan quality is frequently compromised by pati

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel

arXiv:2604.10157v1 Announce Type: cross Abstract: Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant

Active Inference with a Self-Prior in the Mirror-Mark Task

arXiv:2604.09673v1 Announce Type: cross Abstract: The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an

researcharxiv-cs-ai

AmodalSVG: Amodal Image Vectorization via Semantic Layer Peeling

arXiv:2604.10940v1 Announce Type: new Abstract: We introduce AmodalSVG, a new framework for amodal image vectorization that produces semantically organized and geometrically complete SVG representatio

AnySlot: Goal-Conditioned Vision-Language-Action Policies for Zero-Shot Slot-Level Placement

model-releasesarxiv-cs-ro

arXiv:2604.10432v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies have emerged as a versatile paradigm for generalist robotic manipulation. However, precise object placement under

ATANT v1.1: Positioning Continuity Evaluation Against Memory, Long-Context, and Agentic-Memory Benchmarks

arXiv:2604.10981v1 Announce Type: new Abstract: ATANT v1.0 (arXiv:2604.06710) defined continuity as a system property with 7 required properties and introduced a 10-checkpoint, LLM-free evaluation met

Attention-Guided Dual-Stream Learning for Group Engagement Recognition: Fusing Transformer-Encoded Motion Dynamics with Scene Context via Adaptive Gating

arXiv:2604.10078v1 Announce Type: new Abstract: Student engagement is crucial for improving learning outcomes in group activities. Highly engaged students perform better both individually and contribu

researcharxiv-cs-cv

Autonomous Diffractometry Enabled by Visual Reinforcement Learning

arXiv:2604.11773v1 Announce Type: cross Abstract: Automation underpins progress across scientific and industrial disciplines. Yet, automating tasks requiring interpretation of abstract visual informat

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Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation

arXiv:2510.12460v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided co

Beyond Matching to Tiles: Bridging Unaligned Aerial and Satellite Views for Vision-Only UAV Navigation

arXiv:2603.22153v3 Announce Type: replace-cross Abstract: Recent advances in cross-view geo-localization (CVGL) methods have shown strong potential for supporting unmanned aerial vehicle (UAV) navigat

BezierFlow: Learning Bezier Stochastic Interpolant Schedulers for Few-Step Generation

arXiv:2512.13255v3 Announce Type: replace Abstract: We introduce BezierFlow, a lightweight training approach for few-step generation with pretrained diffusion and flow models. BezierFlow achieves a 2-

researcharxiv-cs-lg

Binary Flow Matching: Prediction-Loss Space Alignment for Robust Learning

arXiv:2602.10420v2 Announce Type: replace Abstract: Flow matching has emerged as a powerful framework for generative modeling, with recent empirical successes highlighting the effectiveness of signal-

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BLADE: Bayesian Langevin Active Discovery with Replica Exchange for Identification of Complex Systems

arXiv:2503.02983v2 Announce Type: replace-cross Abstract: Traditional methods for system discovery frequently struggle with efficient data usage and uncertainty quantification. Identifying the governi

BRIDGE and TCH-Net: Heterogeneous Benchmark and Multi-Branch Baseline for Cross-Domain IoT Botnet Detection

arXiv:2604.11324v1 Announce Type: cross Abstract: IoT botnet detection has advanced, yet most published systems are validated on a single dataset and rarely generalise across environments. Heterogeneo

C2F-Thinker: Coarse-to-Fine Reasoning with Hint-Guided Reinforcement Learning for Multimodal Sentiment Analysis

arXiv:2604.00013v2 Announce Type: replace-cross Abstract: Multimodal sentiment analysis aims to integrate textual, acoustic, and visual information for deep emotional understanding. Despite the progre

CableTract: A Co-Designed Cable-Driven Field Robot for Low-Compaction, Off-Grid Capable Agriculture

arXiv:2604.09938v1 Announce Type: cross Abstract: Conventional field operations spend most of their energy moving the tractor body, not the implement. Yet feasibility studies for novel agricultural ve

researcharxiv-cs-lg