Search: “papers”

State Space Models Meet Remote Sensing: A Survey

arXiv:2606.25329v1 Announce Type: new Abstract: State Space Models (SSMs), designed for long-range modeling, offer linear computational complexity and strong capabilities in capturing long-range depen

25 Jun 2026

The Effective Number of Nonzeros: Theory and Regularization for Sparse Recovery

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DGX agent

arXiv:2603.13826v2 Announce Type: replace Abstract: Classical sparse recovery treats all nonzero entries equally, though numerical noise often creates long tails of negligible coefficients. This paper

researcharxiv-cs-lg

25 Jun 2026

A Robust Model-Based Approach for Continuous-Time Policy Evaluation with Unknown Levy Process Dynamics

arXiv:2504.01482v3 Announce Type: replace-cross Abstract: This paper develops a model-based framework for continuous-time policy evaluation (CTPE) in reinforcement learning, incorporating both Brownia

safetyarxiv-cs-lg

Automatic Part-of-Speech Tagging of Arabic-English Dictionary Senses through WordNet

arXiv:2606.24359v1 Announce Type: new Abstract: This paper proposed an algorithm for part-of-speech (POS) tagging senses of a bilingual dictionary. The algorithm is applied on the Al-Mawrid Arabic-Eng

researcharxiv-cs-cl

Local Ai

Deep numerical schemes for systems of Ergodic BSDEs with applications to regime-switching forward utilities

arXiv:2606.24271v1 Announce Type: cross Abstract: In this paper, we introduce two neural-network-based numerical schemes for solving systems of coupled ergodic Backward Stochastic Differential Equatio

local-aiarxiv-cs-lg

Difference-Making without Making a Difference

arXiv:2606.24832v1 Announce Type: new Abstract: Over a series of seven papers, Andreas & Gunther have introduced seven definitions of actual causation and have classified them as belonging to three di

Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirability

arXiv:2606.23701v1 Announce Type: cross Abstract: Qualitative product feedback can reveal nuanced user experiences, but its implicit sentiment is difficult to measure. This paper presents a scalable a

Explaining Failures of Cyber-Physical Systems with Actual Causality

arXiv:2606.24546v1 Announce Type: new Abstract: Modern autonomous Cyber-Physical Systems (CPSs), such as self-driving cars, face increasingly complex demands, and yet are expected to act reliably. The

agentsarxiv-cs-ro

Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering

arXiv:2403.04890v4 Announce Type: replace Abstract: In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without optio

researcharxiv-cs-cl

From Singleton Obstacles to Clutter: Translation Invariant Compositional Avoid Sets

arXiv:2603.22146v2 Announce Type: replace-cross Abstract: This paper studies obstacle avoidance under translation invariant dynamics using an avoid-side travel cost Hamilton Jacobi formulation. For ru

Geometry-Aware Style Transfer in 3D Gaussian Splatting

arXiv:2606.24144v1 Announce Type: new Abstract: In this paper, we present a novel geometry-aware style transfer framework for 3D Gaussian splatting (3DGS) that simultaneously transfers appearance attr

Governed Shared Memory for Multi-Agent LLM Systems

arXiv:2606.24535v1 Announce Type: new Abstract: Multi-agent LLM environments require robust mechanisms for shared knowledge management. This paper formalizes the fleet-memory problem and identifies fo

safetyarxiv-cs-ai

Infinitesimal Causality

arXiv:2606.24621v1 Announce Type: cross Abstract: This paper introduces a categorical account of infinitesimal causality in Frobenius Markov categories equipped with tangent-bundle semantics. IDC capt

Measuring User's Mental Models of Speech Translation in Human-AI Collaboration

arXiv:2606.24644v1 Announce Type: new Abstract: Millions of people use machine translation (MT) tools daily, yet little is known about their perception of what systems can and cannot do. This paper st

researcharxiv-cs-cl

Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles

arXiv:2505.02281v3 Announce Type: replace-cross Abstract: This paper explores the performance of a random Gaussian smoothing zeroth-order (ZO) scheme for minimising quasar-convex (QC) and strongly qua

One Ruler: A Same-Hands Re-Evaluation of Bivariate Causal Direction on Tuebingen, with a Parameter-Free Compression Baseline

arXiv:2606.23767v1 Announce Type: new Abstract: Headline accuracies on the Tuebingen cause-effect pairs are routinely compared across papers even though each is measured under its authors' own protoco

Topological Online Learning for Displacement-based Formation Control

arXiv:2606.23901v1 Announce Type: new Abstract: This paper addresses the problem of robust formation control by introducing Topological Online Learning for Displacement-based (TOLD) formation control,

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

UOL@IDEM at BEA 2026 Shared Task 1: Neural Fusion and Feature-Rich Modeling for L1-Aware Vocabulary Difficulty Prediction

arXiv:2606.24501v1 Announce Type: new Abstract: This paper describes UOL@IDEM's closed-track submission to the BEA 2026 shared task on L1-aware vocabulary difficulty prediction. We model the task as r

safetyarxiv-cs-cl

Varying Bundle Size Reactive Multi-Task Assignment using Selective Cost Estimation for Multi-Agent Systems

arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall

agentsarxiv-cs-ro

Applications

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

applicationsarxiv-cs-cv

Which Spaces can be Embedded in L_p-type Reproducing Kernel Banach Space? A Characterization via Metric Entropy

arXiv:2410.11116v4 Announce Type: replace-cross Abstract: In this paper, we establish a novel connection between the metric entropy growth and the embeddability of function spaces into reproducing ker

A Reward-Petri-Net Interpretation of Temporal Behavior Trees

arXiv:2606.21350v1 Announce Type: new Abstract: This paper introduces an interpretation of Temporal Behavior Trees (TBTs) as Reward-Petri-Nets (RPNs) for reinforcement learning (RL). Designing reward

A Test-time Actor-Critic Approach to News Images Generation

arXiv:2606.21304v1 Announce Type: new Abstract: This paper introduces the CERTH-ITI solution for the MediaEval NewsImages 2026 challenge, which focuses on generating images related to news headlines.

Achieving widetilde{O}(1/epsilon) Sample Complexity for Bilinear Systems Identification under Bounded Noises

arXiv:2603.20819v2 Announce Type: replace Abstract: This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances.

Hardware

An Analysis of Untrained Deep Reservoir Networks for Audio Surveillance

arXiv:2606.22218v1 Announce Type: cross Abstract: In this paper, we investigate untrained recurrent models from the Reservoir Computing (RC) paradigm for audio surveillance, focusing on bidirectional

hardwarearxiv-cs-lg

Applications

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

applicationsarxiv-cs-cv

Bracing for Impact: Robust Humanoid Push Recovery and Locomotion with Reduced Order Models

arXiv:2505.11495v2 Announce Type: replace Abstract: Push recovery during locomotion will facilitate the deployment of humanoid robots in human-centered environments. In this paper, we present a unifie

Bridging Semantics and Kinematics: A Modular Framework for Zero-Shot Robotic Manipulation

arXiv:2606.23157v1 Announce Type: new Abstract: This paper presents a modular training-free framework for zero-shot, language-guided robotic manipulation in semi-structured environments. The architect

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces

arXiv:2507.15741v2 Announce Type: replace-cross Abstract: This paper introduces a framework for uncertainty quantification in regression models defined on metric spaces. Using a proposed notion of hom

Convergence Analysis of Nystrom Subsampling in Covariate Shift Adaptation for Misspecified case

arXiv:2606.22259v1 Announce Type: cross Abstract: This paper investigates convergence properties of regularized Nystrom subsampling applied to the unsupervised domain adaptation problem under covariat

Data Evolution by Wittgenstein's Rule Following

arXiv:2606.22674v1 Announce Type: cross Abstract: This paper introduces Wittgenstein's Rule Following (WRF) data evolution, a framework in philomatics for evolving or generating a new dataset from a s

Deep Learning for Individual Heterogeneity

arXiv:2010.14694v4 Announce Type: replace-cross Abstract: This paper integrates deep neural networks (DNNs) into structural models to increase flexibility and capture rich heterogeneity while preservi

safetyarxiv-cs-lg

Direct Raw Audio Signal Processing via Reservoir Computing: An Investigation into 'Feature-Free' Architectures

arXiv:2606.21335v1 Announce Type: cross Abstract: This paper evaluates Reservoir Computing (RC) as an autonomous, 'feature-free' framework for audio processing, designed to eliminate traditional, hand

agentsarxiv-cs-lg

Discrete Geometric Modeling and Extended State Estimation of Continuum Robots

arXiv:2606.21205v1 Announce Type: cross Abstract: In this paper, we present a fully discrete approach for the accurate and numerically efficient dynamical modeling and state estimation of continuum ro

DR-Mamba: Automatic Inference-Time Domain Adaptation for Document Image Binarization via Sample-Conditioned Detail-Background Suppression

model-releasesarxiv-cs-cv

arXiv:2606.22625v1 Announce Type: new Abstract: Degraded document image binarization is sensitive to domain shifts caused by paper aging, bleed-through, stains, shadows, and uneven illumination, and t

Dual-Stream EEG Decoding for 3D Visual Perception

arXiv:2606.22182v1 Announce Type: new Abstract: This paper explores a novel brain decoding model for 3D shape perception through a dual pathway architecture mirroring biological vision. Our bio-inspir

Dynamics, stability, and energy efficiency of an energy-recycling rimless wheel with spring-clutch legs

model-releasesarxiv-cs-ro

arXiv:2606.22073v1 Announce Type: new Abstract: This paper proposes an energy-recycling rimless wheel with spring-clutch legs. The proposed mechanism uses a lockable clutch to store part of the impact

Enhancing IMU-Based Online Handwriting Recognition via Contrastive Learning with Zero Inference Overhead

arXiv:2602.07049v2 Announce Type: replace Abstract: Online handwriting recognition using inertial measurement units opens up handwriting on paper as input for digital devices. Doing it on edge hardwar

safetyarxiv-cs-cv

Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis

arXiv:2508.17142v3 Announce Type: replace-cross Abstract: This paper proposes a frequency-domain estimator for low-order systems from repeated noisy measurements. The estimator minimizes a quadratic d

Full Nonlinear Nonholonomic Dynamics and Motion Analysis of a 3-DoF Underactuated Spherical Rolling Robot

arXiv:2606.22169v1 Announce Type: new Abstract: This paper presents a full nonlinear constrained dynamic model of MonoRollBot, a novel 3-DoF spherical rolling robot driven by a single motor, a lead-sc

Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems

arXiv:2505.00909v3 Announce Type: replace Abstract: In this paper, we propose a Gaussian Process (GP)-based policy iteration framework for addressing both forward and inverse problems in Hamilton--Jac

safetyarxiv-cs-lg

Generating Fearful Images: Investigating Potential Emotional Biases in Image-Generation Models

model-releasesarxiv-cs-cv

arXiv:2411.05985v3 Announce Type: replace-cross Abstract: This paper examines potential biases and inconsistencies in the emotions evoked by images produced by generative artificial intelligence (AI)

GenTrack: A New Generation of Multi-Object Tracking

arXiv:2510.24399v3 Announce Type: replace Abstract: This paper introduces a novel multi-object tracking (MOT) method, dubbed GenTrack, whose main contributions include: first-a hybrid tracking approac

agentsarxiv-cs-cv

Kiwano: A Cutting-Edge Open-Source Toolkit for Speaker Verification

arXiv:2606.22369v1 Announce Type: cross Abstract: In this paper, we present Kiwano, an open-source toolkit designed to advance research and evaluation for speaker verification. Kiwano provides a light

Learning-Augmented Algorithms for Online Vertex Cover

arXiv:2606.22831v1 Announce Type: cross Abstract: This paper studies learning-augmented online weighted vertex cover with advice and a parameter lambda in (0,1). We consider two graph cases: bipartite

LLM-Based Generalizable Hierarchical Task Planning and Execution for Heterogeneous Robot Teams with Event-Driven Replanning

model-releasesarxiv-cs-ro

arXiv:2511.22354v2 Announce Type: replace Abstract: This paper introduces CoMuRoS (Collaborative Multi-Robot System), a generalizable hierarchical architecture for heterogeneous robot teams that unifi

Non-asymptotic estimates of the minimal risk in statistical learning

arXiv:2606.23295v1 Announce Type: new Abstract: In this paper we prove some concentration inequalities for two types of error probabilities in the Empirical Risk Principle (ERP) in statistical learnin