Search: “papers”

EB-gMCR: Energy-Based Generative Modeling for Signal Unmixing and Multivariate Curve Resolution

arXiv:2507.23600v5 Announce Type: replace Abstract: A single measurement of a chemical mixture, a reaction mixture, a natural extract, or a tissue, records the sum of the profiles of the few component

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Agents

EcoBoat: Design and Experimental Validation of an Autonomous Body-Board Boat For Cleaning Water Bodies

DGX agent

arXiv:2609.14450v1 Announce Type: new Abstract: Cleaning water bodies such as swimming pools and lakes typically demands significant manual effort or reliance on costly, sensor-intensive robotic syste

agentsarxiv-cs-ro

15 Sept 2026

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents

arXiv:2609.15422v1 Announce Type: new Abstract: AI agents are provisioned the same as employee-owned hosts in many enterprise settings with a static credential set fixed at deployment which includes a

End-to-End Cell Detection via Instance-aware Graph Modeling

arXiv:2609.15354v1 Announce Type: cross Abstract: Accurate cell detection and classification are crucial for pathological analysis, directly affecting diagnostic accuracy and treatment planning. To ca

Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving

arXiv:2512.10159v3 Announce Type: replace-cross Abstract: LLMs have shown strong performance in data-rich domains such as programming, but their reliability in engineering tasks remains limited. Circu

Event-Level Emotion Recognition in the Wild Using Deep Facial Expression Analysis

arXiv:2609.13854v1 Announce Type: new Abstract: Facial emotion recognition (FER) in real-world environments remains challenging due to unconstrained imaging conditions, including multiple faces, occlu

applicationsarxiv-cs-cv

EvoOntology: A Self-Evolving Ontology Layer for Data Agents

arXiv:2609.15779v1 Announce Type: new Abstract: Data agents aim to fulfill natural-language instructions over heterogeneous data, including tables, files, and databases. However, data agents face a ch

agentsarxiv-cs-ai

Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language Models

arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach

Exploring Multimodal Turn-Taking Cues in Face-to-Face Conversation using Voice Activity Projection

arXiv:2609.14666v1 Announce Type: cross Abstract: Turn-taking is a fundamental component of spoken interaction, and while humans naturally rely on both verbal and non-verbal signals, dialogue systems

Exploring napping paradigm for Recurrent Spiking Neural Networks

arXiv:2609.13927v1 Announce Type: new Abstract: Biological organisms minimize free energy by balancing two competing demands on their internal world model: it must be accurate enough to predict sensor

FedV-KGQA in Practice: Design Lessons and an Interactive Prototype

arXiv:2609.13661v1 Announce Type: new Abstract: Knowledge graph question answering usually assumes that one system can reach the whole graph. In practice, facts are often held by organizations that sh

Finite-Time Node Separation in Recurrent Graph Neural Networks with Persistent Gaussian Perturbations

arXiv:2609.13920v1 Announce Type: cross Abstract: Persistent Gaussian perturbations have been shown to prevent asymptotic oversmoothing in recurrent Graph Neural Networks (GNNs) by ensuring a positive

Force-Aware Reinforcement Learning with Hybrid Sensorless Force Estimation for Wheeled-Legged Loco-Manipulation

arXiv:2609.13779v1 Announce Type: new Abstract: Force-controlled loco-manipulation requires a whole-body policy to coordinate locomotion and arm motion while regulating end-effector interaction forces

safetyarxiv-cs-ro

Tutorials

From Token Probabilities to Semantic Constraints: Towards Declarative Probabilistic Evaluation of Language Models

arXiv:2609.13520v1 Announce Type: new Abstract: While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they ac

tutorialsarxiv-cs-cl

Fusing Spectral Signatures and Activation Clustering for Backdoor Detection in Healthcare Imaging Models: Method, Implementation, and Evaluation

model-releasesarxiv-cs-lg

arXiv:2609.14290v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in healthcare imaging pipelines for diagnostic support, and training-time attacks against them are a

Gap Entropy and Almost Instance-Wise Optimal Best-Arm Identification

arXiv:2609.13703v1 Announce Type: cross Abstract: In the best-arm identification problem, we are given n stochastic arms with unknown means and wish to identify the arm with the largest mean with prob

GEAR: From Dynamic Encoding to Dynamic Activation in Social Trajectory Prediction

arXiv:2609.13778v1 Announce Type: cross Abstract: Human trajectory prediction requires modeling both individual motion patterns and social interactions among agents. Existing methods have made substan

safetyarxiv-cs-ai

GradRepair-ODE: Certified Gradient Repair for Neural ODE Training

arXiv:2609.13204v1 Announce Type: cross Abstract: Neural ordinary differential equations use numerical solvers inside the training loop. The solver determines the forward trajectory and also affects t

Graph Neural Networks for Influence Maximization in Social Networks: An Unsupervised Minimum Dominating Set Approach

arXiv:2609.13836v1 Announce Type: new Abstract: The Minimum Dominating Set (MDS) problem is a classic NP-hard combinatorial optimization problem with critical applications in social network analysis,

applicationsarxiv-cs-lg

Graph-Transformer Fraud Detection with Self-Supervised Pretraining and Conformal Risk Control

arXiv:2609.14234v1 Announce Type: cross Abstract: Financial fraud in corporate transaction networks has grown more coordinated and harder to detect with rule-based engines and with classical learning

GSLAD: Prototype-Regularized Graph Structure Learning for Multivariate Time Series Anomaly Detection

arXiv:2609.15483v1 Announce Type: new Abstract: Unsupervised multivariate time series anomaly detection methods typically identify anomalies through forecasting, reconstruction, or representation disc

Hierarchical Deep Counterfactual Regret Minimization

arXiv:2305.17327v4 Announce Type: replace Abstract: Imperfect Information Games (IIGs) are used to model games under uncertainty or lack complete information. Counterfactual Regret Minimization (CFR)

How User-AI Mistreatment Occurs and Matters in Conversational Systems?

arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding

safetyarxiv-cs-ai

How Well Do Pseudo-Rigid Body Models Capture Real Plants? In-Field Validation of Simulated Blueberry Canes

arXiv:2609.13627v1 Announce Type: new Abstract: Many labor-intensive tasks in fruit production such as pruning require physically interacting with the plant (e.g., pushing, pulling, bending limbs, etc

applicationsarxiv-cs-ro

Human-Grounded Calibration for Long-Text Image-Text Congruence in Vision-Language Models

arXiv:2609.15640v1 Announce Type: cross Abstract: Long-text image--text congruence scoring is increasingly important for vision-language systems that must evaluate whether detailed textual description

IMM-based Multiple Object Tracking using a State Prediction Neural Network

arXiv:2609.13307v1 Announce Type: cross Abstract: Object tracking is essential for autonomous vehicles to avoid obstacles and plan routes. Radar maintains detection performance even in adverse weather

agentsarxiv-cs-ai

Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification

arXiv:2609.15145v1 Announce Type: new Abstract: The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning ca

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

arXiv:2605.05271v2 Announce Type: replace-cross Abstract: LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer revie

applicationsarxiv-cs-ai

Hardware

Is Semantic SLAM Ready for Embedded Systems ? A Comparative Survey

arXiv:2505.12384v2 Announce Type: replace Abstract: Semantic SLAM holds promise for robust robot navigation in complex environments, but its practicality on embedded systems remains uncertain. This pa

hardwarearxiv-cs-ro

JSolver: Joint Spectrum Estimation and Multi-Material Decomposition from Single-Energy CT Projections

arXiv:2505.08123v2 Announce Type: replace-cross Abstract: Multi-material decomposition (MMD) enables quantitative reconstruction of tissue compositions in the human body, supporting a wide range of cl

safetyarxiv-cs-ai

KnowBench: Effort Reduction as a Unified, Deployment-Grounded Benchmark for Clinical AI

arXiv:2609.15794v1 Announce Type: new Abstract: Clinical AI systems are evaluated with instruments built for research settings (reference-based similarity metrics and expert rubric panels) that measur

L-Lipschitz Gershgorin ResNet Network

arXiv:2502.21279v2 Announce Type: replace-cross Abstract: Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradi

LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents

arXiv:2609.13437v1 Announce Type: new Abstract: Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to

Leakage-Safe and Scheduler-Aware Machine Learning for Grid Job Runtime Prediction

arXiv:2609.13701v1 Announce Type: cross Abstract: Accurate job runtime prediction can improve scheduling-aware resource management in grid and distributed computing environments, but prediction models

Learning Agile Flight Maneuvers: Deep SE(3) Motion Planning and Control for Quadrotors

arXiv:2209.11097v2 Announce Type: replace Abstract: Agile flights of autonomous quadrotors in cluttered environments require constrained motion planning and control subject to translational and rotati

safetyarxiv-cs-ro

Learning from Reliable Negatives: Confidence-Anchored Test-Time Adaptation for GUI Grounding

arXiv:2609.15307v1 Announce Type: new Abstract: Graphical User Interface (GUI) grounding is essential for autonomous agents to map natural language instructions to precise screen coordinates. However,

agentsarxiv-cs-cv

Learning Multi-Agent Task Assignment and Navigation in the Factory: from Simulation to Real Robots

arXiv:2609.14567v1 Announce Type: cross Abstract: Reinforcement learning (RL) has shown considerable promise for robotic decision-making, yet deploying multi-agent RL (MARL) on physical multi-robot sy

safetyarxiv-cs-lg

LLaTSA: Large Language Model-Aligned General-Purpose Transient Stability Analysis

arXiv:2609.14374v1 Announce Type: cross Abstract: Dynamic trajectory prediction has become an important paradigm for data-driven transient stability analysis (TSA), yet most existing predictors remain

LLM-Enhanced Multi-Agent Reinforcement Learning for Unified Electric Vehicles-Charging Station-Grid Optimization in Public Charging Systems

arXiv:2609.13805v1 Announce Type: new Abstract: In the era of the Internet of Things (IoT), coordinating connected electric vehicle (EV) charging scheduling to balance EV charging satisfaction, statio

agentsarxiv-cs-ai

Map Users and Mapmakers: The Scope of Cognitive Attribution from Acquired Representations

arXiv:2609.13879v1 Announce Type: new Abstract: An acquired representation can enlarge a system's cognitive repertoire without transferring the capacities exercised in producing that representation. T

MCIQA-2K: A Multi-Dimensional Dataset and No-Reference Quality Assessment Benchmark for Colorized Images

model-releasesarxiv-cs-cv

arXiv:2609.14495v1 Announce Type: new Abstract: Image colorization is an inherently ill-posed task, since a single grayscale image may correspond to multiple plausible colorized results. Consequently,

Measuring the Creativity of Frontier LLMs in Automated Research

arXiv:2609.14057v1 Announce Type: new Abstract: Frontier LLMs are increasingly capable of conducting automated research, yet their creativity in this setting has not been systematically evaluated. In

Medical Knowledge Simplification for Patients in the Era of LLMs: A Case Study on Diabetes

arXiv:2609.15129v1 Announce Type: new Abstract: Complex medical information is often difficult for patients to understand, making effective medical knowledge simplification essential for improving pat

applicationsarxiv-cs-ai

MedTRACE: Tool-Augmented Multimodal Clinical Reasoning Agents for Evidence-Grounded Decision-Making

arXiv:2609.14823v1 Announce Type: new Abstract: Multimodal clinical decision-making requires reliable reasoning over heterogeneous evidence from electronic health records, medical images, and physiolo

agentsarxiv-cs-cl

Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding

model-releasesarxiv-cs-cv

arXiv:2609.13991v1 Announce Type: new Abstract: Reconstructing 3D objects from brain signals offers a promising avenue for understanding human visual cognition. While prior work has shown initial succ

Minibatch persistency, eight years later: what batch reuse costs in steps and joules, and what it saves in data

model-releasesarxiv-cs-lg

arXiv:2609.13922v1 Announce Type: new Abstract: Minibatch persistency reuses data instead of reading it: rather than drawing a fresh minibatch at every optimizer step, it takes K consecutive steps on

Mizan: A National Benchmark for Evaluating Large Language Models on Iraqi Arabic and the Iraqi Civic Context

arXiv:2609.13980v1 Announce Type: cross Abstract: Arabic large-language-model (LLM) evaluation has matured around Modern Standard Arabic (MSA): aggregated leaderboards such as the Open Arabic LLM Lead