Search: “applications”

FM-G-CAM: A Holistic Approach for Explainable AI in Computer Vision

arXiv:2312.05975v3 Announce Type: replace-cross Abstract: Explainability is a vital aspect of modern AI for real-world impact and usability. The main objective of this paper is to emphasise the need t

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Applications

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning

DGX agent

arXiv:2605.15299v1 Announce Type: cross Abstract: In search and recommendation systems, predictive models often suffer from temporal instability when certain input features introduce volatility in out

applicationsarxiv-cs-ai

18 May 2026

Greedy or not, here I come: Language production under vocabulary constraints in humans and resource-rational models

arXiv:2605.15365v1 Announce Type: new Abstract: Communicating using only a limited vocabulary is a common but challenging cognitive phenomenon, requiring an ideal communicator to plan carefully to opt

applicationsarxiv-cs-cl

ITGPT: Generative Pretraining on Irregular Timeseries

arXiv:2605.16069v1 Announce Type: new Abstract: Timeseries regression models often struggle to leverage large volumes of labeled multimodal data, particularly when the data are irregularly sampled or

LAPS: Improving Incremental LiDAR Mapping using Active Pooling and Sampling for Neural Distance Fields

arXiv:2605.15496v1 Announce Type: cross Abstract: Neural distance fields offer a compact and continuous representation of 3D geometry, making them attractive for incremental LiDAR mapping. However, th

Research

Layer Selection in Feature-Based Losses Affects Image Quality and Microstructural Consistency in Deep Learning Super-Resolution of Brain Diffusion MRI

arXiv:2605.15895v1 Announce Type: cross Abstract: Clinical application of high-resolution diffusion MRI is hindered by hardware limitations and prohibitive scan times, motivating computational super-r

researcharxiv-cs-cv

Layer-wise Derivative Controlled Networks

arXiv:2605.15463v1 Announce Type: new Abstract: As machine learning models grow in complexity, they increasingly struggle with three conflicting demands: the need for high accuracy, the requirement fo

Learning Dynamic Pick-and-Place for a Legged Manipulator

arXiv:2605.15713v1 Announce Type: cross Abstract: Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achiev

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity

arXiv:2605.15242v1 Announce Type: new Abstract: The reliability of Healthcare Information Systems (HIS) is frequently compromised by human-induced data entry errors, which existing statistical anomaly

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing

arXiv:2509.20349v3 Announce Type: replace Abstract: Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control, yet deep learning models

RealRep: Generalized SDR-to-HDR Conversion via Attribute-Disentangled Representation Learning

arXiv:2505.07322v4 Announce Type: replace Abstract: High-Dynamic-Range Wide-Color-Gamut (HDR-WCG) technology is becoming increasingly widespread, driving a growing need for converting Standard Dynamic

Reasoners or Translators? Contamination-aware Evaluation and Neuro-Symbolic Robustness in Tax Law

arXiv:2605.16052v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly enhanced automated legal reasoning. Yet, it remains unclear whether their performance

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building

arXiv:2605.15630v1 Announce Type: cross Abstract: Free energy profiles serve as a fundamental bridge between microscopic atomic fluctuations and macroscopic thermodynamic observables. Estimating the f

Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics

arXiv:2605.15465v1 Announce Type: new Abstract: Physiological time series signals reflect complex, multi-scale dynamical processes of the human body. Existing modeling studies focus on static tasks su

Unified Simulation of Lagrangian Particle Dynamics via Transformer

arXiv:2605.15305v1 Announce Type: cross Abstract: A unified simulator that can model diverse physical phenomena without solver-specific redesign is a long-standing goal across simulation science. We p

Research

Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity

arXiv:2511.03606v2 Announce Type: replace-cross Abstract: The study of self-normalized processes plays a crucial role in a wide range of applications, from sequential decision-making to econometrics.

researcharxiv-cs-lg

Wind-Aware Optimal Trajectory Planning for Efficient Gliding of Fixed-Wing Aerial Systems

arXiv:2605.15619v1 Announce Type: new Abstract: Gliding offers small fixed-wing UAVs extended endurance and silent operation but requires accurate energy management, especially under wind disturbances

applicationsarxiv-cs-ro

A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights

arXiv:2511.05159v2 Announce Type: replace-cross Abstract: Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's k-means, without requiring a

A Novel Schur-Decomposition-Based Weight Projection Method for Stable State-Space Neural-Network Architectures

arXiv:2605.14489v1 Announce Type: new Abstract: Building black-box models for dynamical systems from data is a challenging problem in machine learning, especially when asymptotic stability guarantees

Model Releases

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection

model-releasesarxiv-cs-ai

arXiv:2511.18739v2 Announce Type: replace Abstract: Time series anomaly detection is widely used in IoT and cyber-physical systems, yet its evaluation remains challenging due to diverse application ob

An Interpretable Latency Model for Speculative Decoding in LLM Serving

arXiv:2605.15051v1 Announce Type: new Abstract: Speculative decoding (SD) accelerates large language model (LLM) inference by using a smaller draft model to propose multiple tokens that are verified b

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

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

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

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