Search: “applications”

arXiv:2604.14398v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) are a promising propulsion concept that may offer higher thermodynamic efficiency and specific impulse than convent

agentsarxiv-cs-lg

17 Apr 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity

DGX agent

arXiv:2507.23121v2 Announce Type: replace Abstract: In this work, we study a critical research problem regarding the trustworthiness of large language models (LLMs): how LLMs behave when encountering

model-releasesarxiv-cs-cl

17 Apr 2026

WaveSFNet: A Wavelet-Based Codec and Spatial--Frequency Dual-Domain Gating Network for Spatiotemporal Prediction

arXiv:2603.23284v2 Announce Type: replace Abstract: Spatiotemporal predictive learning aims to forecast future frames from historical observations in an unsupervised manner, and is critical to a wide

17 Apr 2026

A Bayesian Framework for Uncertainty-Aware Explanations in Power Quality Disturbance Classification

arXiv:2604.13658v1 Announce Type: new Abstract: Advanced deep learning methods have shown remarkable success in power quality disturbance (PQD) classification. To enhance model transparency, explainab

Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning

arXiv:2512.08639v3 Announce Type: replace Abstract: Aerial Vision-and-Language Navigation (VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and navigate c

An Empirical Investigation of Practical LLM-as-a-Judge Improvement Techniques on RewardBench 2

arXiv:2604.13717v1 Announce Type: new Abstract: LLM-as-a-judge, using a language model to score or rank candidate responses, is widely used as a scalable alternative to human evaluation in RLHF pipeli

Automated co-design of high-performance thermodynamic cycles via graph-based hierarchical reinforcement learning

arXiv:2604.13133v1 Announce Type: new Abstract: Thermodynamic cycles are pivotal in determining the efficacy of energy conversion systems. Traditional design methodologies, which rely on expert knowle

Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting

arXiv:2604.13253v1 Announce Type: new Abstract: Adaptive Conformal Inference (ACI) provides distribution-free prediction intervals with asymptotic coverage guarantees for time series under distributio

Boundary Sampling to Learn Predictive Safety Filters via Pontryagin's Maximum Principle

arXiv:2604.13325v1 Announce Type: new Abstract: Safety filters provide a practical approach for enforcing safety constraints in autonomous systems. While learning-based tools scale to high-dimensional

safetyarxiv-cs-ro

C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions

arXiv:2604.13521v1 Announce Type: new Abstract: Neural network models with latent recurrent processing, where identical layers are recursively applied to the latent state, have gained attention as pro

Capability-Aware Heterogeneous Control Barrier Functions for Decentralized Multi-Robot Safe Navigation

arXiv:2604.13245v1 Announce Type: new Abstract: Safe navigation for multi-robot systems requires enforcing safety without sacrificing task efficiency under decentralized decision-making. Existing dece

safetyarxiv-cs-ro

Computational framework for multistep metabolic pathway design

arXiv:2604.13471v1 Announce Type: new Abstract: In silico tools are important for generating novel hypotheses and exploring alternatives in de novo metabolic pathway design. However, while many comput

Convex Hulls of Reachable Sets

arXiv:2303.17674v5 Announce Type: replace-cross Abstract: We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets pl

Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source

arXiv:2511.13417v2 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries from satellite imagery is essential for land management and crop monitoring, yet existing meth

Depth-Aware Image and Video Orientation Estimation

arXiv:2604.13995v1 Announce Type: new Abstract: This paper introduces a novel approach for image and video orientation estimation by leveraging depth distribution in natural images. The proposed metho

safetyarxiv-cs-cv

DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis

arXiv:2604.13416v1 Announce Type: new Abstract: Advances in radiance fields have enabled photorealistic novel view synthesis. In several domains, large-scale real-world datasets have been developed to

DiffMagicFace: Identity Consistent Facial Editing of Real Videos

arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid

Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics

arXiv:2604.13366v1 Announce Type: new Abstract: Accurate modeling of robot dynamics is essential for model-based control, yet remains challenging under distributional shifts and real-time constraints.

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection

arXiv:2604.13899v1 Announce Type: new Abstract: Instruction-tuned LLMs can annotate thousands of instances from a short prompt at negligible cost. This raises two questions for active learning (AL): c

Does Dimensionality Reduction via Random Projections Preserve Landscape Features?

arXiv:2604.13230v1 Announce Type: new Abstract: Exploratory Landscape Analysis (ELA) provides numerical features for characterizing black-box optimization problems. In high-dimensional settings, howev

EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

model-releasesarxiv-cs-lg

arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi

Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression

arXiv:2604.13410v1 Announce Type: cross Abstract: We study the problem of estimating the effect function for a continuous treatment, which maps each treatment value to a population-averaged outcome. A

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi

Getting the Numbers Rightnicode{x2014}Modelling Multi-Class Object Counting in Dense and Varied Scenes

arXiv:2510.02213v2 Announce Type: replace Abstract: Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In mult

HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization

arXiv:2604.13179v1 Announce Type: cross Abstract: This paper presents HUANet, a constrained deep neural network architecture that unrolls the iterations of the Alternating Direction Method of Multipli

Hybrid Retrieval for COVID-19 Literature: Comparing Rank Fusion and Projection Fusion with Diversity Reranking

arXiv:2604.13728v1 Announce Type: cross Abstract: We present a hybrid retrieval system for COVID-19 scientific literature, evaluated on the TREC-COVID benchmark (171,332 papers, 50 expert queries). Th

IndicDB -- Benchmarking Multilingual Text-to-SQL Capabilities in Indian Languages

arXiv:2604.13686v1 Announce Type: new Abstract: While Large Language Models (LLMs) have significantly advanced Text-to-SQL performance, existing benchmarks predominantly focus on Western contexts and

LaoBench: A Large-Scale Multidimensional Lao Benchmark for Large Language Models

arXiv:2511.11334v3 Announce Type: replace Abstract: The rapid advancement of large language models (LLMs) has not been matched by their evaluation in low-resource languages, especially Southeast Asian

Leveraging LLM-GNN Integration for Open-World Question Answering over Knowledge Graphs

arXiv:2604.13979v1 Announce Type: new Abstract: Open-world Question Answering (OW-QA) over knowledge graphs (KGs) aims to answer questions over incomplete or evolving KGs. Traditional KGQA assumes a c

Med-CAM: Minimal Evidence for Explaining Medical Decision Making

arXiv:2604.13695v1 Announce Type: new Abstract: Reliable and interpretable decision-making is essential in medical imaging, where diagnostic outcomes directly influence patient care. Despite advances

safetyarxiv-cs-cv

Multistage Conditional Compositional Optimization

arXiv:2604.14075v1 Announce Type: cross Abstract: We introduce Multistage Conditional Compositional Optimization (MCCO) as a new paradigm for decision-making under uncertainty that combines aspects of

Local Ai

Nested Fourier-enhanced neural operator for efficient modeling of radiation transfer in fires

arXiv:2604.13919v1 Announce Type: cross Abstract: Computational fluid dynamics (CFD) has become an essential tool for predicting fire behavior, yet maintaining both efficiency and accuracy remains cha

local-aiarxiv-cs-lg

node2vec or triangle-biased random walks: stationarity, regularity & recurrence

arXiv:2604.13681v1 Announce Type: cross Abstract: The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random w

On an L^2 norm for stationary ARMA processes

arXiv:2408.10610v5 Announce Type: replace Abstract: We propose an L^2 norm for stationary Autoregressive Moving Average (ARMA) models. We look at ARMA models within the Hilbert space of the past with

Pareto-Optimal Offline Reinforcement Learning via Smooth Tchebysheff Scalarization

arXiv:2604.13175v1 Announce Type: new Abstract: Large language models can be aligned with human preferences through offline reinforcement learning (RL) on small labeled datasets. While single-objectiv

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines

arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly

PBE-UNet: A light weight Progressive Boundary-Enhanced U-Net with Scale-Aware Aggregation for Ultrasound Image Segmentation

arXiv:2604.13791v1 Announce Type: new Abstract: Accurate lesion segmentation in ultrasound images is essential for preventive screening and clinical diagnosis, yet remains challenging due to low contr

Person Re-Identification via Generalized Class Prototypes

arXiv:2510.17043v2 Announce Type: replace Abstract: Advanced feature extraction methods have significantly contributed to enhancing the task of person re-identification. In addition, modifications to

Physics-Informed Neural Networks for Solving Derivative-Constrained PDEs

arXiv:2604.13723v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) recast PDE solving as an optimisation problem in function space by minimising a residual-based objective, yet m

Red Skills or Blue Skills? A Dive Into Skills Published on ClawHub

arXiv:2604.13064v1 Announce Type: new Abstract: Skill ecosystems have emerged as an increasingly important layer in Large Language Model (LLM) agent systems, enabling reusable task packaging, public d

Local Ai

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework

arXiv:2604.13994v1 Announce Type: new Abstract: Generative diffusion priors have recently achieved state-of-the-art performance in natural image super-resolution, demonstrating a powerful capability t

local-aiarxiv-cs-cv

Robust Low-Rank Tensor Completion based on M-product with Weighted Correlated Total Variation and Sparse Regularization

model-releasesarxiv-cs-lg

arXiv:2604.13525v1 Announce Type: cross Abstract: The robust low-rank tensor completion problem addresses the challenge of recovering corrupted high-dimensional tensor data with missing entries, outli

Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis

arXiv:2511.14755v2 Announce Type: replace-cross Abstract: As perception-based controllers for autonomous systems become increasingly popular in the real world, it is important that we can formally ver

RPS: Information Elicitation with Reinforcement Prompt Selection

model-releasesarxiv-cs-lg

arXiv:2604.13817v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable capabilities in dialogue generation and reasoning, yet their effectiveness in eliciting user-known bu

SceneGlue: Scene-Aware Transformer for Feature Matching without Scene-Level Annotation

arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained

SocialMirror: Reconstructing 3D Human Interaction Behaviors from Monocular Videos with Semantic and Geometric Guidance

arXiv:2604.13581v1 Announce Type: new Abstract: Accurately reconstructing human behavior in close-interaction scenarios is crucial for enabling realistic virtual interactions in augmented reality, pre

SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models

arXiv:2510.09541v3 Announce Type: replace Abstract: Diffusion large language models (dLLMs) are emerging as an efficient alternative to autoregressive models due to their ability to decode multiple to

safetyarxiv-cs-cl

Swap Regret Minimization Through Response-Based Approachability

arXiv:2602.06264v2 Announce Type: replace Abstract: We consider the problem of minimizing different notions of swap regret in online optimization. These forms of regret are tightly connected to correl