Search: “papers”

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

Let the smart horses build their own harness. See my previous article on this: https://x.com/Kangwook_Lee/status/2052925157606568217 🧠Self-Harness: Harnesses that improve themselves New paper on agent

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

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

arXiv:2606.22491v1 Announce Type: new Abstract: This paper presents 'PenduMorph', a wireless reconfigurable rolling spherical robot designed as a modular platform for enclosed locomotion and inter-mod

arXiv:2606.23175v1 Announce Type: new Abstract: AI scientist systems are described as tools, coauthors, or founders, but we evaluate them as if only the final answer matters. This position paper argue

arXiv:2511.23221v2 Announce Type: replace Abstract: In this paper, we challenge the conventional notion in 3DGS-SLAM that rendering quality is the primary determinant of tracking accuracy. We argue th

arXiv:2602.08690v2 Announce Type: replace Abstract: Deep Reinforcement Learning (DRL) has achieved remarkable success in domains requiring sequential decision-making, motivating its application to cyb

arXiv:2503.22087v3 Announce Type: replace Abstract: In this paper, we explore dense voxel streaming for accurate and efficient 3D occupancy prediction. While dense voxel representations offer fine-gra

arXiv:2606.23548v1 Announce Type: cross Abstract: This paper presents SuperCond-GNN, a graph neural network-based surrogate model for predicting the voltage distribution in high-temperature supercondu

arXiv:2606.20647v1 Announce Type: new Abstract: This paper presents Tessellated Biomes, a cyber-physical framework for the adaptive robotic construction and reconfiguration of modular multi-material a

arXiv:2606.20600v1 Announce Type: cross Abstract: What can the success of modern AI tell us about how humans learn? This paper argues that taking AI seriously as a model of human learning supports a m

arXiv:2602.01448v2 Announce Type: replace Abstract: This paper introduces a novel robotic system designed to manage severe bleeding in emergency scenarios, including unique environments like space sta

arXiv:2606.23371v1 Announce Type: new Abstract: For imitation learning in robotic manipulation, high data collection costs result in the scarcity of high quality data. In this paper, we leverage the i

arXiv:2606.22976v1 Announce Type: new Abstract: In this paper, we propose using random walks on graphs as a verifiable sandbox to study different parallel sampling strategies in masked diffusion model

arXiv:2606.21385v1 Announce Type: new Abstract: This paper explores unsupervised disentangled representation learning from a functional perspective. We define latent concepts as factors that influence

'When an LLM outputs a step-by-step plan, it creates a powerful illusion that you are watching a machine reason its way to a conclusion. A position paper by professor Subbarao Kambhampati and research

arXiv:2606.11672v1 Announce Type: cross Abstract: This paper explores the value of agentic AI tools for cybersecurity purposes. We evaluate the efficacy of a general-purpose GenAI Large Language Model

arXiv:2606.11916v1 Announce Type: cross Abstract: This paper proposes an empirical methodology to study software aging in GPU-based LLM serving systems. Traditional aging studies focus on CPU-centric

arXiv:2606.11952v1 Announce Type: new Abstract: This paper introduces a novel tactile sensor for in-hand manipulation with slip-aware control that integrates velocity, force/torque, and pressure map s

arXiv:2606.11798v1 Announce Type: cross Abstract: In this paper, we develop a continuous-time model-free reinforcement learning algorithm to learn deterministic equilibrium policies in general time-in

arXiv:2606.11687v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified o

arXiv:2606.11968v1 Announce Type: new Abstract: This paper studies efficient online algorithms for multinomial logistic bandits (MLogB), where the feedback distribution over K+1 outcomes follows a mul

arXiv:2606.11710v1 Announce Type: new Abstract: This paper presents ERN-Net, an Evolving Reason Node-Net for efficient document image binarization. ERN-Net enhances degradation-sensitive regions, such

arXiv:2606.12277v1 Announce Type: new Abstract: In this paper, we propose an approach to finding sets of similar-performing models (in terms of loss/accuracy measurements) with highly different contex

arXiv:2606.12295v1 Announce Type: cross Abstract: This overview paper presents the results of the shared task for the second workshop on Multimodal Augmented Generation via Multimodal Retrieval (MAGMa

arXiv:2606.11652v1 Announce Type: new Abstract: This paper investigates reinforcement learning (RL) methods for improving tool-calling capabilities in multimodal small language model (SLM) agents. Whi

arXiv:2606.11884v1 Announce Type: new Abstract: This paper addresses the challenge of assessing image quality in ID cards in remote verification systems by applying capture-related quality measures fr

arXiv:2606.11474v1 Announce Type: new Abstract: In this paper, we study Mahalanobis-guided latent out-of-distribution (OOD) detection for test-time RL controller switching in nonlinear time-varying sy

arXiv:2606.12047v1 Announce Type: cross Abstract: In this paper, we address the problem of zero-shot understanding of accidents from surveillance videos by identifying when an impact event occurs, wha

arXiv:2606.11596v1 Announce Type: cross Abstract: In this paper, we consider a class of networked systems comprising an interconnected set of linear subsystems, disturbance inputs, and performance out

arXiv:2606.11278v1 Announce Type: new Abstract: In this paper, we introduce the Soft Lamprey-Inspired Dual Environment Robot (SLIDER) and a proper modeling and optimization procedure employed to desig

arXiv:2606.12106v1 Announce Type: cross Abstract: This paper presents our solution to the 2026 SoccerNet VQA Challenge. We first develop a cost-effective data synthesis pipeline driven by a Vision-Lan