Search: “applications”

FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters

arXiv:2606.24113v1 Announce Type: new Abstract: Federated unlearning (FU) is critical for complying with legal mandates like the right to be forgotten in decentralized systems, yet current methods fac

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Model Releases

FlowerDance: MeanFlow for Efficient and Refined 3D Dance Generation

DGX agent

arXiv:2511.21029v3 Announce Type: replace Abstract: Music-to-dance generation aims to translate auditory signals into expressive human motion, with broad applications in virtual reality, choreography,

model-releasesarxiv-cs-cv

24 Jun 2026

GRACE: Gated Refinement for Accurate Causal Edge Discovery in High-Dimensional Time Series

arXiv:2606.23880v1 Announce Type: new Abstract: From climate teleconnections to gene regulation, modern time-series datasets encompass tens or hundreds of interacting variables, making causal discover

Legible and Intuitive Multi-modal Robot State and Intent Communication Validated in Online and Real-world Studies

arXiv:2606.24445v1 Announce Type: new Abstract: Effective robot-to-human communication can increase transparency and trust, reduce uncertainty, and contribute to safer collaboration in shared workspac

applicationsarxiv-cs-ro

Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching

arXiv:2606.24457v1 Announce Type: new Abstract: Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computation, or additional foundation-model

MATCH: Flow Matching for Multi-View Anomaly Detection

arXiv:2606.24375v1 Announce Type: new Abstract: Detecting anomalies in industrial objects is an important topic for increasing production efficiency. More complex objects often require the analysis of

Model Releases

MortarBench: Evaluating Mortgage Loan Origination Agents

model-releasesarxiv-cs-lg

arXiv:2606.19416v2 Announce Type: replace Abstract: Loan origination is the process by which a lender creates a new loan, from application and underwriting through approval and funding. This process s

Natural Identifiers for Privacy and Data Audits in Large Language Models

arXiv:2606.24408v1 Announce Type: new Abstract: Assessing the privacy of large language models (LLMs) presents significant challenges. In particular, most existing methods for auditing differential pr

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials

arXiv:2505.21916v3 Announce Type: replace Abstract: Embodied robots have achieved strong performance in many real-world manipulation tasks, yet agile dynamic manipulation remains challenging due to hi

applicationsarxiv-cs-ro

QSignAI: Quantum-Randomness-Seeded Identity Signatures at the Intersection of AI for Science and Science for AI

arXiv:2605.27729v3 Announce Type: replace-cross Abstract: The 2024-2025 Nobel and Turing awards recognised AI and quantum science simultaneously. Yet no deployed system has brought these streams toget

Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image

arXiv:2606.24138v1 Announce Type: new Abstract: Generating explicit 3D city assets from a single satellite image is important for digital twins, urban simulation, and geospatial intelligence. Unlike s

SemChunk-C: Semantic Segmentation for C Code

arXiv:2606.23697v1 Announce Type: cross Abstract: Semantic segmentation of code written in a C-family language remains a challenging problem, due to the language's complex syntax, macro expansion, and

SLEEPING-DISCO 9M: A large-scale pre-training dataset for generative music modeling

arXiv:2506.14293v4 Announce Type: replace-cross Abstract: We present Sleeping-DISCO 9M, a large-scale pre-training dataset for music and song. To the best of our knowledge, there are no open-source hi

Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching

arXiv:2606.24824v1 Announce Type: new Abstract: Modeling chaotic systems is crucial yet challenging. Inverse problems in chaotic dynamics, namely inferring initial conditions from final states, remain

The impact of generative artificial intelligence on academic development of Chinese students in humanities and social sciences

arXiv:2606.24104v1 Announce Type: cross Abstract: Generative artificial intelligence(GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and

The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs

arXiv:2504.17768v3 Announce Type: replace Abstract: Sparse attention offers a promising strategy to extend long-context capabilities in Transformer LLMs, yet its efficiency-accuracy trade-offs remain

applicationsarxiv-cs-cl

Towards Federated Long-Tailed Graph Learning: An Energy-Guided Dual Decoupling Approach

arXiv:2606.24237v1 Announce Type: new Abstract: Federated Graph Learning facilitates collaborative graph modeling across distributed clients while preserving data privacy. However, real-world data cat

TuringViT: Making SOTA Vision Transformers Accessible to All

arXiv:2606.24253v1 Announce Type: new Abstract: Modern VLMs and VLA systems commonly adopt off-the-shelf ViTs such as SigLIP2 as visual encoders, but diverse downstream requirements in latency, tempor

Research

Uniform Sampling from High-dimensional Spectral Norm Balls

arXiv:2606.24134v1 Announce Type: cross Abstract: Motivated by an application in machine learning optimization, this paper focuses on the challenges of sampling a matrix uniformly from the unit spectr

researcharxiv-cs-lg

VisChronos: Revolutionizing Image Captioning Through Real-Life Events

arXiv:2606.24058v1 Announce Type: new Abstract: This paper aims to bridge the semantic gap between visual content and natural language understanding by leveraging historical events in the real world a

ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering

arXiv:2606.24602v1 Announce Type: new Abstract: Despite remarkable progress in multimodal understanding, current MLLMs still exhibit limitations in video text understanding, particularly when semantic

A Completion-Aware Framework for Impactful Counterfactual Explainability in Graph Neural Networks

arXiv:2606.22033v1 Announce Type: new Abstract: In this study, we propose a novel pipeline for generic, model-agnostic, local-level counterfactual explainability in graph neural networks (GNNs). Altho

A Lightweight MPC Bidding Framework for Brand Auction Ads

arXiv:2603.07721v2 Announce Type: replace-cross Abstract: Brand advertising plays a critical role in building long-term consumer awareness and loyalty, making it a key objective for advertisers across

A new classification method based on Minimum Spanning Trees

arXiv:2606.21639v1 Announce Type: new Abstract: Minimum Spanning Trees have been used in unsupervised learning, particularly in clustering tasks, due to their ability to recognize clusters by removing

A Novel Approach to Temporal QoS Estimation via Extended Kalman Filter-Incorporated Latent Feature Analysis

arXiv:2606.23010v1 Announce Type: new Abstract: Predicting temporal Quality of Service (QoS) data is critical for optimizing network services and rationalizing resource allocation in cloud computing a

A Physics-Informed, Behavior-Aware Digital Twin for Robust Multimodal Forecasting of Core Body Temperature in Precision Livestock Farming

arXiv:2604.04098v2 Announce Type: replace Abstract: Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study pr

A polarity-aware multi-relational model for the signed interaction prediction in biological networks

arXiv:2407.07357v4 Announce Type: replace Abstract: Predicting signed interactions in biological networks is crucial for understanding drug mechanisms and facilitating drug repurposing. While deep gra

A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning

arXiv:2603.13293v2 Announce Type: replace Abstract: Accurate cardiovascular risk prediction is crucial for preventive healthcare; however, the development of robust Artificial Intelligence (AI) models

AdaPrivate-TS: Private Thompson Sampling for Contextual Bandits with Privacy Amplification

arXiv:2606.21757v1 Announce Type: new Abstract: We present AdaPrivate-TS, a differentially private contextual bandit algorithm that combines Thompson Sampling with batched zCDP composition. Our key in

An Efficient and Effective Architecture for Large-Scale Traffic Prediction via Geometry-Adaptive Square Partitioning

arXiv:2606.21072v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making. Despite the effectiveness of mainstream neural-

Analysis and Prediction of At-Risk Students Using Machine Learning Algorithms

arXiv:2606.20617v1 Announce Type: cross Abstract: Student attrition represents a significant challenge for higher education institutions because it impacts both academic results and financial viabilit

ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software

arXiv:2408.02153v2 Announce Type: replace-cross Abstract: Achieving reproducibility, quantity, and diversity in vulnerability datasets has long been viewed as an inherent three-way trade-off, where im

ASC-SW: A Lightweight Atrous Strip Convolution Network for DLOs Segmentation on Edge mobile Robots

arXiv:2507.12744v4 Announce Type: replace Abstract: Detecting deformable linear objects (DLOs), such as floor cables, is essential for safe mobile robot navigation but remains challenging due to obliq

applicationsarxiv-cs-ro

Bayesian three-dimensional seismic travel-time tomography for active- and passive-source seismic data using physics-informed neural network

arXiv:2606.21789v1 Announce Type: cross Abstract: Accurate 3D seismic velocity modeling through seismic travel-time tomography using both active- and passive-source data provides critical underpinning

Betting on Moments: Legendre Jumper Martingales for Online Exchangeability Testing

arXiv:2606.20859v1 Announce Type: cross Abstract: We present a family of conformal test martingales based on shifted Legendre polynomials, which extends the Simple Jumper martingale. The Simple Legend

BEV-Denoise: Learning Intrinsic Noise for Accurate Bird's-Eye-View Semantic Segmentation

arXiv:2606.22931v1 Announce Type: new Abstract: In this paper, we present a framework dubbed extbf{BEV-Denoise} that estimates and removes intrinsic noise from learned Bird's-Eye-View (BEV) features t

Beyond a Single Light: A Large-Scale Aerial Dataset for Urban Scene Reconstruction Under Varying Illumination

arXiv:2512.14200v2 Announce Type: replace Abstract: Recent advances in Neural Radiance Fields and 3D Gaussian Splatting have demonstrated strong potential for large-scale UAV-based 3D reconstruction t

Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning

arXiv:2606.22171v1 Announce Type: new Abstract: Epidemic forecasting models typically rely on surveillance data reported over administrative regions, treating them as atomic units, thereby obscuring s

Bridging Single Distortion Artifacts and Multifactorial Clinical Quality: Few-shot Biparametric MRI Quality Assessment via Distortion-trained Prototypical Networks

arXiv:2606.18872v2 Announce Type: replace Abstract: Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation

arXiv:2606.21413v1 Announce Type: cross Abstract: Nowadays, large multilingual translation models demonstrate impressive translation capabilities in the machine translation benchmarks. This raises a p

CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching

arXiv:2410.12261v5 Announce Type: replace Abstract: Anomaly detection in multivariate time series is challenging as heterogeneous subsequence anomalies may occur. Reconstruction-based methods, which f

CELEUS: Certifiable and Efficient LLM Evaluation via E-Processes

arXiv:2606.20820v1 Announce Type: new Abstract: Can we trust evaluation scores to capture an LLM's true real-world performance? Certifiable evaluation answers this question by providing guarantee for

Changing Modalities: Adapting Remote Sensing Models to New Satellites and Sensors

arXiv:2606.23356v1 Announce Type: new Abstract: Machine learning models for remote sensing are trained and deployed on a static set of modalities. However, as we equip newer satellites with novel sens

Combinatorial Sparse PCA Beyond the Spiked Identity Model

arXiv:2603.02607v2 Announce Type: replace-cross Abstract: Sparse PCA is one of the most well-studied problems in high-dimensional statistics. In this problem, we are given samples from a distribution

Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning

arXiv:2602.22642v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) has substantially empowered Large Language Models (LLMs) to tackle complex reasoning tasks, yet the verbose nature of explici

Context-Aware Autoregressive Diffusion for Gloss-Wise Sign Language Production

arXiv:2606.21234v1 Announce Type: new Abstract: To generate natural and accurate sentence-level sign language, synthesizing the 'gloss', the fundamental semantic unit, is essential. However, most curr

Detection and Evaluation of Clusters within Sequential Data

arXiv:2210.01679v2 Announce Type: replace Abstract: Sequential data is ubiquitous -- it is routinely gathered to gain insights into complex processes such as behavioral, biological, or physical proces

Development and Design of FLKit: A Structured Onboarding Toolkit for Federated Learning in Health and Life Sciences

arXiv:2606.23500v1 Announce Type: cross Abstract: Federated learning lets institutions train shared models without moving their data, which makes it a natural fit for health and life sciences research