Search: “applications”

Any3D-VLA: Enhancing VLA Robustness via Diverse Point Clouds

arXiv:2602.00807v2 Announce Type: replace Abstract: Existing Vision-Language-Action (VLA) models typically take 2D images as visual input, which limits their spatial understanding in complex scenes. H

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Applications

Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge

DGX agent

arXiv:2505.09246v4 Announce Type: replace-cross Abstract: In many real-world settings, machine learning models and interactive systems have access to both structured knowledge, e.g., knowledge graphs

applicationsarxiv-cs-ai

15 May 2026

Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning

arXiv:2605.14049v1 Announce Type: new Abstract: The growing adoption of large language models in legal practice brings both significant promise and serious risk. Legal professionals stand to benefit f

CAKE: Confidence in Assignments via K-partition Ensembles

arXiv:2602.18435v2 Announce Type: replace Abstract: Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagn

CalibAnyView: Beyond Single-View Camera Calibration in the Wild

arXiv:2605.14615v1 Announce Type: new Abstract: Camera calibration is a fundamental prerequisite for reliable geometric perception, yet classical approaches rely on controlled acquisition setups that

CoCo-InEKF: State Estimation with Learned Contact Covariances in Dynamic, Contact-Rich Scenarios

arXiv:2605.15122v1 Announce Type: cross Abstract: Robust state estimation for highly dynamic motion of legged robots remains challenging, especially in dynamic, contact-rich scenarios. Traditional app

Comparative Evaluation of Machine Learning Approaches for Minority-Class Financial Distress Prediction Under Class Imbalance Constraints

arXiv:2605.14067v1 Announce Type: new Abstract: Financial distress prediction remains a significant challenge in enterprise risk analysis due to the highly imbalanced nature of real-world financial da

Safety

Comparing Developer and LLM Biases in Code Evaluation

arXiv:2603.24586v2 Announce Type: replace-cross Abstract: As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial

safetyarxiv-cs-cl

Contrastive Multi-Modal Hypergraph Reasoning for 3D Crowd Mesh Recovery

arXiv:2605.13854v1 Announce Type: new Abstract: Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Cur

Cross-Domain Few-Shot Segmentation via Ordinary Differential Equations over Time Intervals

arXiv:2509.01299v2 Announce Type: replace Abstract: Cross-domain few-shot segmentation (CD-FSS) aims to segment unseen categories with very limited samples while alleviating the negative effects of do

CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision

arXiv:2605.14171v1 Announce Type: new Abstract: Channel state information (CSI) provides a widely available sensing modality for human and environment perception, but existing CSI sensing models usual

Model Releases

Derivation Prompting: A Logic-Based Method for Improving Retrieval-Augmented Generation

model-releasesarxiv-cs-ai

arXiv:2605.14053v1 Announce Type: cross Abstract: The application of Large Language Models to Question Answering has shown great promise, but important challenges such as hallucinations and erroneous

Does Synthetic Layered Design Data Benefit Layered Design Decomposition?

arXiv:2605.15167v1 Announce Type: new Abstract: Recent advances in image generation have made it easy to produce high-quality images. However, these outputs are inherently flattened, entangling foregr

DT-Transformer: A Foundation Model for Disease Trajectory Prediction on a Real-world Health System

arXiv:2605.14227v1 Announce Type: cross Abstract: Accurate disease trajectory prediction is critical for early intervention, resource allocation, and improving long-term outcomes. While electronic hea

applicationsarxiv-cs-cl

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks

arXiv:2502.00270v3 Announce Type: replace-cross Abstract: The performance of an LLM depends heavily on the relevance of its training data to the downstream evaluation task. However, in practice, the d

Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology

arXiv:2605.14258v1 Announce Type: cross Abstract: Large language models are remarkably capable, yet how computation propagates through their layers remains poorly understood. A growing line of work tr

Energy-Regularized Sequential Model Editing on Hyperspheres

arXiv:2510.01172v3 Announce Type: replace Abstract: Large language models (LLMs) require constant updates to remain aligned with evolving real-world knowledge. Model editing offers a lightweight alter

applicationsarxiv-cs-cl

Enhanced and Efficient Reasoning in Large Learning Models

arXiv:2605.14036v1 Announce Type: new Abstract: In current Large Language Models we can trust the production of smoothly flowing prose on the basis of the principles of machine learning. However, ther

Evidential Reasoning Advances Interpretable Real-World Disease Screening

arXiv:2605.15171v1 Announce Type: cross Abstract: Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima

Finding Interpretable Prompt-Specific Circuits in Language Models

arXiv:2602.13483v2 Announce Type: replace-cross Abstract: Understanding the internal circuits that language models use to solve tasks remains a central challenge in mechanistic interpretability. A cru

From Sparse to Dense: Spatio-Temporal Fusion for Multi-View 3D Human Pose Estimation with DenseWarper

arXiv:2605.14525v1 Announce Type: new Abstract: In multi-view 3D human pose estimation, models typically rely on images captured simultaneously from different camera views to predict a pose at a speci

From Street View to Visual Network: Mapping the Visibility of Urban Landmarks with Vision-Language Models

arXiv:2505.11809v3 Announce Type: replace Abstract: Visibility analysis in urban planning has traditionally relied on line-of-sight (LoS) simulations, which capture geometric occlusion. However, these

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

arXiv:2605.14445v1 Announce Type: new Abstract: Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tas

H-OmniStereo: Zero-Shot Omnidirectional Stereo Matching with Heading-Aligned Normal Priors

arXiv:2605.14963v1 Announce Type: new Abstract: Stereo matching on top-bottom equirectangular images provides an effective framework for full-surround perception, as vertically aligned epipolar lines

ImmuVis: Hyperconvolutional Foundation Model for Imaging Mass Cytometry

arXiv:2602.04585v2 Announce Type: replace Abstract: We present ImmuVis, a family of efficient foundation models for imaging mass cytometry (IMC), a high-throughput multiplex imaging technology that ha

LEAP: Local ECT-Based Learnable Positional Encodings for Graphs

arXiv:2510.00757v3 Announce Type: replace Abstract: Graph neural networks (GNNs) largely rely on the message-passing paradigm, where nodes iteratively aggregate information from their neighbors. Yet,

Learning with Shallow Neural Networks on Cluster-Structured Features

arXiv:2605.14927v1 Announce Type: new Abstract: The success of deep learning in high-dimensional settings is often attributed to the presence of low-dimensional structure in real-world data. While sta

Manifold Dimension Estimation via Local Graph Structure

arXiv:2510.15141v4 Announce Type: replace-cross Abstract: Most existing manifold dimension estimators rely on the assumption that the underlying manifold is locally flat within the neighborhoods under

Masked Autoencoders with Limited Data: Does It Work? A Fine-Grained Bioacoustics Case Study

arXiv:2605.14031v1 Announce Type: cross Abstract: Bioacoustic recognition requires fine-grained acoustic understanding to distinguish similar-sounding species. However, many large-scale data repositor

MultiMat: Multimodal Program Synthesis for Procedural Materials using Large Multimodal Models

arXiv:2509.22151v3 Announce Type: replace Abstract: Material node graphs are programs that generate the 2D channels of procedural materials, including geometry such as roughness and displacement maps,

Optimal Pattern Detection Tree for Symbolic Rule-Based Classification

arXiv:2605.14374v1 Announce Type: cross Abstract: Pattern discovery in data plays a crucial role across diverse domains, including healthcare, risk assessment, and machinery maintenance. In contrast t

ReasonCache: Accelerating Large Reasoning Model Serving through KV Cache Sharing

arXiv:2507.21433v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) are becoming integral to many AI inference systems, enhancing their capabilities with advanced reasoning. Howeve

Scalable Krylov Subspace Methods for Generalized Mixed-Effects Models with Crossed Random Effects

arXiv:2505.09552v3 Announce Type: replace-cross Abstract: Mixed-effects models are widely used to model data with hierarchical grouping structures and high-cardinality categorical predictor variables.

Research

Scalable Solution of the Stochastic Multi-path Traveling Salesman Problem via Neural Networks

arXiv:2605.14662v1 Announce Type: cross Abstract: The multi-path Traveling Salesman Problem with stochastic travel costs arises in hybrid vehicle routing applications designed for Smart City and City

researcharxiv-cs-lg

SCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation

arXiv:2605.14926v1 Announce Type: new Abstract: Achieving pixel-level accurate segmentation of structural cracks across diverse scenarios remains a formidable challenge. Existing methods face signific

SEDGE: Structural Extrapolated Data Generation

arXiv:2604.02482v2 Announce Type: replace Abstract: This paper aims to address the challenge of data generation beyond the training data and proposes a framework for Structural Extrapolated Data GEner

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

arXiv:2510.16196v2 Announce Type: replace-cross Abstract: Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to

Self-Regulated Learning in Essay Writing: Consistency of Strategies and Impact on Outcomes

arXiv:2605.14228v1 Announce Type: cross Abstract: Background: Abilities for effective self-regulated learning (SRL) are critical for lifelong learning, particularly during adolescence when these skill

Silent Neuron Theory and Plasticity Preservation for Deep Reinforcement Learning in Adaptive Video Streaming

arXiv:2505.01584v3 Announce Type: replace-cross Abstract: Adaptive video streaming optimizes Quality of Experience (QoE) metrics by selecting appropriate bitrates according to varying network bandwidt

SoFFT: Spatial Fourier Transform for Modeling Continuum Soft Robots

arXiv:2502.17347v2 Announce Type: replace Abstract: Continuum soft robots, composed of flexible materials, exhibit theoretically infinite degrees of freedom, enabling notable adaptability in unstructu

applicationsarxiv-cs-ro

Spectral Analysis of Fake News Propagation

arXiv:2605.13861v1 Announce Type: cross Abstract: The propagation structure of fake news has been shown to be an important cue for detecting it; yet, existing propagation-based fake news detection met

SuperADD: Training-free Class-agnostic Anomaly Segmentation -- CVPR 2026 VAND 4.0 Workshop Challenge Industrial Track

arXiv:2605.14808v1 Announce Type: new Abstract: Visual anomaly detection (AD) for industrial inspection is a highly relevant task in modern production environments. The problem becomes particularly ch

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting

arXiv:2605.14069v1 Announce Type: new Abstract: Irregularly sampled multivariate event streams remain a stubbornly difficult modality for generative modeling: tokenization-based approaches break down

SyncLight: Single-Edit Multi-View Relighting

arXiv:2601.16981v2 Announce Type: replace Abstract: We present SyncLight, a method to enable consistent, parametric control over light sources across multiple uncalibrated views of a static scene cond

TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering

arXiv:2601.21656v3 Announce Type: replace Abstract: Clustering tabular data is a fundamental yet challenging problem due to heterogeneous feature types, diverse data-generating mechanisms, and the abs

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

arXiv:2410.02091v3 Announce Type: replace-cross Abstract: Generative artificial intelligence (AI) facilitates content production and enhances ideation capabilities, which can significantly influence d

The Potential of Convolutional Neural Networks for Cancer Detection

arXiv:2412.17155v4 Announce Type: replace Abstract: Early detection is crucial for successful cancer treatment and increasing survivability rates, particularly in the most common forms. Ten different

Model Releases

TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes

model-releasesarxiv-cs-lg

arXiv:2605.14915v1 Announce Type: new Abstract: Imbalanced learning remains a fundamental challenge in tabular data applications. Despite decades of research and numerous proposed algorithms, a system