Search: “applications”

Planar Symmetric Pattern Generation

arXiv:2606.02073v1 Announce Type: new Abstract: Generating objects with specific symmetries is essential in various real-world scenarios. However, adapting existing 2D continuous representations to en

2 Jun 2026

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach

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arXiv:2606.01012v1 Announce Type: new Abstract: AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions.

applicationsarxiv-cs-ai

2 Jun 2026

Symmetries in PAC-Bayesian Learning

arXiv:2510.17303v2 Announce Type: replace Abstract: Symmetries are known to improve the empirical performance of machine learning models, yet theoretical guarantees explaining these gains remain limit

2 Jun 2026

Which Institutional Frameworks Do Chatbots Assume? Auditing Jurisdictional Defaults in Multilingual LLMs

arXiv:2606.00333v1 Announce Type: new Abstract: LLMs increasingly answer questions about taxes, labor protections, healthcare, education, pensions, and administrative procedures, where usefulness ofte

applicationsarxiv-cs-cl

2 Jun 2026

Feature-Aware (Hyper)graph Generation via Next-Scale Prediction

arXiv:2506.01467v3 Announce Type: replace Abstract: Graph generative models perform well on small structured data but struggle to scale to large, complex structures. Hierarchical approaches improve sc

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis

arXiv:2501.12500v3 Announce Type: replace Abstract: Understanding climate dynamics requires going beyond correlations in observational data to uncover the underlying causal process. Latent drivers suc

Performance and Complexity Trade-off Optimization of Speech Models During Training

arXiv:2601.13704v3 Announce Type: replace-cross Abstract: In speech machine learning, neural network models are typically designed by choosing an architecture with fixed layer sizes and structure. The

SAM for Robust Mitochondria Instance Segmentation in Fluorescence Microscopy

arXiv:2605.31284v1 Announce Type: cross Abstract: The morphological analysis of mitochondria in fluorescence microscopy (FM) is crucial for understanding cellular health, energy production, and metabo

The Challenges of Using Reinforcement Learning for Controlling Industrial Energy Systems

arXiv:2605.31044v1 Announce Type: new Abstract: Reinforcement learning has shown promising results for optimizing the control of industrial energy systems, yet most existing studies remain limited to

Model Releases

Cookie-Bench: Continuous On-screen Key Interaction Evaluation for Web Generation

model-releasesarxiv-cs-ai

arXiv:2605.30000v1 Announce Type: new Abstract: Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed

Decentralized LLM-Driven Coordination of Acoustic Robots for Contactless Object Manipulation

arXiv:2605.29378v1 Announce Type: new Abstract: Natural language interfaces can simplify interaction with multi-robot systems, especially when non-expert users need to issue high-level commands. Acous

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces

arXiv:2602.14975v3 Announce Type: replace-cross Abstract: Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS

Gaga: Group Any Gaussians via 3D-aware Memory Bank

arXiv:2404.07977v4 Announce Type: replace Abstract: We introduce Gaga, a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot class-

MOO: A Multi-view Oriented Observations Dataset for Viewpoint Analysis in Cattle Re-Identification

arXiv:2603.04314v2 Announce Type: replace-cross Abstract: Animal re-identification (ReID) faces critical challenges due to viewpoint variations, particularly in Aerial-Ground (AG-ReID) settings where

P^2RAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top-k Retrieval

arXiv:2603.14778v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to use external knowledge, but outsourcing the RAG service raises privacy c

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning

arXiv:2506.08354v2 Announce Type: replace-cross Abstract: This position paper argues that text embedding research should move beyond surface meaning and embrace implicit semantics as a central modelin

Robust and Efficient Writer-Independent IMU-Based Handwriting Recognition

arXiv:2502.20954v3 Announce Type: replace Abstract: Handwriting recognition (HWR) using inertial measurement unit (IMU) data remains challenging due to variations in writing styles and the limited ava

Test Time Training for Supervised Causal Learning

arXiv:2605.30015v1 Announce Type: cross Abstract: Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from signif

Model Releases

A Query Engine for the Agents

model-releasesarxiv-cs-ai

arXiv:2605.27785v1 Announce Type: new Abstract: The fastest-growing data in production today is unstructured text: agent traces, chat logs, reasoning chains, model outputs. People want to analyze it,

A Sheaf-Theoretic and Topological Perspective on Complex Network Modeling and Attention Mechanisms in Graph Neural Models

arXiv:2601.21207v3 Announce Type: replace-cross Abstract: Combinatorial and topological structures, such as graphs, simplicial complexes, and cell complexes, form the foundation of geometric and topol

Context Features Are Cheap: Rank-Aware Decomposition for Efficient Feature Interaction in Recommender Systems

arXiv:2605.27450v1 Announce Type: cross Abstract: Modern industrial recommender systems use a deep ranking model to score N candidates against the same user and context features. Standard implementati

Conveyance: A Versatile Framework for Learning in Structured Class Spaces

arXiv:2605.28420v1 Announce Type: new Abstract: While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-ag

Fine-Tuned LLM as a Complementary Predictor Improving Ads System

arXiv:2605.27856v1 Announce Type: cross Abstract: Recommendation systems power engagement and monetization across feeds, ads, and short-video platforms, but translating the latest advances in Large La

From Causal Discovery to Dynamic Causal Inference in Neural Time Series

arXiv:2603.20980v2 Announce Type: replace-cross Abstract: Time-varying causal models provide a powerful framework for studying dynamic scientific systems, yet most existing approaches assume that the

ObjFiller3D: Scaling 3D Object Inpainting to Dense Multi-View Consistency

arXiv:2508.18271v2 Announce Type: replace Abstract: 3D object inpainting is commonly achieved via multi-view 2D image completion, yet independently inpainted views often suffer from cross-view inconsi

Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization

arXiv:2605.28164v1 Announce Type: cross Abstract: Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simp

Research

RAGe: A Retrieval-Augmented Generation Evaluation Framework

arXiv:2605.27445v1 Announce Type: cross Abstract: Deploying Large Language Model (LLM) applications, particularly those relying on Retrieval-Augmented Generation (RAG), remains challenging due to high

researcharxiv-cs-ai

REC-CBM: Rubric-Aware Error-Correction Concept Bottleneck Models for Trustworthy Open-Ended Grading

arXiv:2605.27402v1 Announce Type: cross Abstract: Open-ended grading is central to equitable and personalized education, yet manual grading remains time-consuming and costly, underscoring the need for

Show, Don't TELL: Explainable AI-Generated Text Detection

arXiv:2605.27921v1 Announce Type: new Abstract: Research on AI-generated text detection has presented a number of approaches to discern human from AI prose, some of which achieving high in-distributio

Simultaneous Contact Selection and Planning for Contact-Rich Manipulation with Cascaded Optimization

arXiv:2605.27972v1 Announce Type: new Abstract: We propose an optimization-based framework for robust contact-rich manipulation. Recent contact-implicit methods enable online hybrid planning across co

Toward Semantic-Agnostic and Shape-Aware Vision-Language Segmentation Models

arXiv:2605.28348v1 Announce Type: new Abstract: Vision-language segmentation models have recently achieved strong performance by leveraging high-level semantic object categories expressed in natural l

Unified Multi-Domain Graph Pre-training for Homogeneous and Heterogeneous Graphs via Domain-Specific Expert Encoding

arXiv:2602.13075v2 Announce Type: replace Abstract: Graph pre-training has achieved remarkable success in recent years, delivering transferable representations for downstream adaptation. However, most

Adapting Actively on the Fly: Relevance-Guided Online Meta-Learning with Latent Concepts for Geospatial Discovery

arXiv:2602.17605v2 Announce Type: replace-cross Abstract: In environmental monitoring, data collection is often costly, sparse, and shaped by urgent public-health needs. This is particularly true for

Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection

arXiv:2506.17633v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection attempts to distinguish outlier samples to prevent models trained on the in-distribution (ID) dataset from

ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

arXiv:2605.25569v2 Announce Type: replace Abstract: Existing deep learning-based low-light enhancement methods are typically trained on limited datasets with single enhancement targets, which restrict

DDGAD: Trajectory Dynamics for Diffusion-Based Graph Anomaly Detection

arXiv:2605.26446v1 Announce Type: cross Abstract: Graph anomaly detection (GAD) aims to identify nodes or substructures whose behavior or attributes deviate significantly from the overall pattern in g

LELA: An End-to-end LLM-based Entity Linking Framework with Zero-shot Domain Adaptation

arXiv:2605.26956v1 Announce Type: new Abstract: Entity linking is a key component of many downstream NLP systems, yet existing approaches are often tied to the specific target knowledge bases and doma

Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks

arXiv:2506.03627v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across various tasks by effectively utilizing a prompting strategy. Howe

Actionable and diverse counterfactual explanations incorporating domain knowledge and plausibility constraints

arXiv:2511.20236v3 Announce Type: replace Abstract: Counterfactual explanations improve the actionable interpretability of machine learning models by identifying minimal changes required to achieve a

CollaBot: Vision-Language Guided Simultaneous Collaborative Manipulation

arXiv:2508.03526v2 Announce Type: replace Abstract: One central goal of robotics is to enable robots to interact with the physical world. Traditional manipulation studies primarily focus on single rob

FLINGO -- Instilling ASP Expressiveness into Linear Integer Constraints

arXiv:2602.09620v2 Announce Type: replace Abstract: Constraint Answer Set Programming (CASP) is a hybrid paradigm that enriches Answer Set Programming (ASP) with numerical constraint processing, a cru

HeLoM: Hierarchical Learning for Whole-Body Loco-Manipulation by a Hexapod Robot

arXiv:2509.23651v3 Announce Type: replace Abstract: In nature, animals often need to move/manipulate objects comparable in weight/size to their own bodies. Compared to grasping and carrying, pushing p

LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability

arXiv:2605.24077v1 Announce Type: cross Abstract: Machine learning deployments in real-world wireless communication tasks face significant generalization challenges due to location and environment-spe

Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints

arXiv:2605.24813v1 Announce Type: new Abstract: Sampling-based model predictive control methods, such as Model Predictive Path Integral (MPPI), offer derivative-free optimization and robustness in com

Overcoming 'Physics Shock' in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference

arXiv:2605.24106v1 Announce Type: cross Abstract: Rapid and accurate flood extent mapping from Remote Sensing data, such as Synthetic Aperture Radar (SAR), is critical for operational disaster respons

PQDT: Pseudo-Query Dual Transformer for Robust Point Cloud Restoration

arXiv:2605.25127v1 Announce Type: cross Abstract: Point clouds are a fundamental 3D representation in computer vision, enabling a wide range of perception tasks. However, real-world point clouds often

What Happens Next? Anticipating Future Motion by Generating Point Trajectories

arXiv:2509.21592v2 Announce Type: replace-cross Abstract: We consider the problem of forecasting motion from a single image, i.e., predicting how objects in the world are likely to move, without the a

Edge Assisted Multi-Camera Vehicle Tracking Framework for Real-Time and Scalable Deployment

arXiv:2511.13904v2 Announce Type: replace Abstract: Cameras are a core sensing modality in modern intelligent transportation systems (ITS), providing rich visual information on road-user activities. M