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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

End-to-End Verifiable and Robust Federated Learning

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DGX agent

arXiv:2609.15521v1 Announce Type: new Abstract: Federated learning enables multiple parties to train a shared model without centralizing raw data with the help of an aggregator, but introduces integri

researcharxiv-cs-lg

15 Sept 2026

Enemray: Toward Capable Language Models for Hassaniya

arXiv:2609.14829v1 Announce Type: cross Abstract: We introduce Enemray, a Hassaniya-centric language model that enables general-purpose interaction in Hassaniya. Enemray is trained around a stability-

Agents

Enhancing Event Candidate Acquisition for Event Linking

arXiv:2609.13670v1 Announce Type: new Abstract: Event linking associates event mentions in text with entries in a knowledge base (KB), or identifies them as out-of-KB events. Although existing methods

agentsarxiv-cs-ai

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

Ensemble Complexity in Photovoltaic Forecasting

arXiv:2609.15049v1 Announce Type: cross Abstract: An ensemble can improve photovoltaic forecasts while adding components that contribute little or increase computation. We assess these effects through

Ensemble-Conditioned Molecular Design

arXiv:2609.15077v1 Announce Type: new Abstract: Molecular design is typically approached as a problem of finding molecules which can adopt a single bioactive conformation. In reality, molecules occupy

Entropy-Punctured Bloom Filters for Memory-Efficient Machine Learning

arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva

Equilibrium bias and convergence in augmented primal--dual dynamics with sampled constraints

arXiv:2609.13925v1 Announce Type: cross Abstract: This work studies the stability and convergence of augmented primal-dual dynamics when constraint values are estimated from samples. Unbiased constrai

safetyarxiv-cs-lg

Tutorials

ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models

arXiv:2609.15089v1 Announce Type: new Abstract: Empathetic response generation in spoken dialogue systems requires both accurate emotion perception and appropriate emotion regulation. Grounded in psyc

tutorialsarxiv-cs-ai

Tutorials

Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial

arXiv:2609.13295v1 Announce Type: cross Abstract: Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data.

tutorialsarxiv-cs-lg

Applications

Ergodic Trajectory Planning with Dynamic Sensor Footprints

arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl

applicationsarxiv-cs-ro

ESAFusion: LiDAR--4-D Radar Fusion via Local Geometric Complementation and Multiscale Adaptive Interaction for 3-D Object Detection

arXiv:2609.14619v1 Announce Type: new Abstract: LiDAR--4-D radar fusion combines accurate spatial geometry with motion and reflectivity cues from radar, offering a promising solution for 3-D object de

researcharxiv-cs-cv

ESG: Generating Physically Consistent Dynamic 3D Scenes from Text Descriptions

model-releasesarxiv-cs-cv

arXiv:2609.15392v1 Announce Type: cross Abstract: Recent progress in image and 3D scene generation has enabled increasingly realistic static environments, yet most methods remain confined to such stat

Estimating Uncertain Spatial Relationships in Robotics

arXiv:1304.3111v2 Announce Type: replace Abstract: In this paper, we describe a representation for spatial information, called the stochastic map, and associated procedures for building it, reading in

Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks

arXiv:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin

Evaluating Contextual Bias in CNN Image Classification: Evidence from Agricultural Benchmark Datasets

model-releasesarxiv-cs-cv

arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based

Evaluating covariate balance for long time horizon Markov decision processes

arXiv:2607.15080v2 Announce Type: replace Abstract: This article explores the application of covariate balance diagnostics for detecting the presence of hidden confounding/model miss-specification in

safetyarxiv-cs-lg

Evaluating LLM-Generated Rules for Heart Disease Prediction

arXiv:2609.13192v1 Announce Type: new Abstract: This study compares traditional machine learning models and Large Language Model (LLM)-generated rule-based systems for heart disease prediction using t

Evaluation Metrics for Safe Reinforcement Learning

arXiv:2609.15315v1 Announce Type: new Abstract: Safe reinforcement learning (RL) is commonly formalized as a Constrained Markov Decision Process (CMDP), in which an agent maximizes expected reward whi

safetyarxiv-cs-ai

Evaluation of MLLM-Agnostic Plug-and-Play Keyframe Selection Methods for Long Video Understanding

arXiv:2609.13250v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) cannot process every frame of a long video because of limitations in visual-token and computational budgets.

Evaluation of optimisation and Bayesian inference methods for reaction rates in atmospheric chemical mechanisms

arXiv:2609.14569v1 Announce Type: cross Abstract: Constraining reaction rate coefficients is a central challenge in the development of explicit atmospheric chemical mechanisms, particularly for autoxi

Applications

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

Event-Native Symbolic-Temporal Spike Encoding Framework for Heterogeneous Cyber Streams

arXiv:2609.15772v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have shown promise for sparse, event-driven computation through stateful processing that is naturally compatible with l

EventVL: Understand Event Streams via Multimodal Large Language Model

arXiv:2501.13707v3 Announce Type: replace-cross Abstract: The event-based Vision-Language Model (VLM) recently has made good progress for practical vision tasks. However, most of these works just util

safetyarxiv-cs-ai

Agents

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

Exact Feasibility Certification and Optimal Responsibility Allocation for Multi-Robot CBF Safety Filters

arXiv:2609.14935v1 Announce Type: new Abstract: Multi-robot Control Barrier Function (CBF) safety filters can become infeasible, but a failed quadratic program (QP) does not indicate why the conflict

safetyarxiv-cs-ro

Exact Finite Attention Responses From RoPE Derivatives

arXiv:2609.14127v1 Announce Type: cross Abstract: We derive exact local responses for attention interventions, allowing candidate edits to be scored from a cached baseline and one backward pass. The s

Exact Recovery by Neighborhood Smoothing in Directed Stochastic Block Models

arXiv:2601.16427v3 Announce Type: replace-cross Abstract: We study exact community recovery in sparse directed stochastic block models using neighborhood smoothing of connection-probability profiles.

Exact Spin Elimination for Quadratic and k-Local Ising Optimization

arXiv:2505.07163v2 Announce Type: replace-cross Abstract: Ising solvers have a finite spin budget. Quadratization uses auxiliary spins to replace higher-order interactions by pairwise ones. We show th

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

researcharxiv-cs-cl

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

Exploring new directions in enhancing the ACTS parameter optimization suite

arXiv:2608.14714v1 Announce Type: cross Abstract: Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are c

Exploring the Potential of Diffusion Large Language Models in Code Generation

arXiv:2509.11252v3 Announce Type: replace-cross Abstract: LLMs have become the mainstream approaches to code generation. Existing LLMs mainly employ autoregressive generation, i.e. generating code tok

Extending the Speed Limit of Quadrupedal Locomotion via Refined Actuator Modeling and Adaptive Command Scheduling

arXiv:2609.13289v1 Announce Type: new Abstract: Achieving high-speed locomotion in quadrupedal robots remains highly challenging, as actuators operate near their physical limits and exhibit pronounced

safetyarxiv-cs-ro

Externalizing Requirement-to-Repair Artifacts as Observable Traces for LLM-Based Program Repair

arXiv:2609.14913v1 Announce Type: new Abstract: Repository-level repair requires not only correct patches but also inspectable records that explain how issue requirements are translated into code chan

Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return

model-releasesarxiv-cs-cl

arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o

Failure-Guided Co-Evolution of Prompts and Training Data

arXiv:2609.15209v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) improves language-model programs by revising prompts from task feedback, yet it typically holds its training data

FaithfulBench: Does AI Counsel Uphold or Undermine the User's Professed Faith?

arXiv:2609.13634v1 Announce Type: cross Abstract: Do AI assistants help believers reason about moral dilemmas consistently with their faith? We present FaithfulBench, the first benchmark to score AI c

Fault Diagnosis for Underwater Vehicles using Moving Horizon Estimation and Gaussian Processes

arXiv:2609.14539v1 Announce Type: new Abstract: This work proposes a model-based fault detection and diagnosis framework for underwater vehicles subject to actuator faults that explicitly accounts for

researcharxiv-cs-ro

Feasibility and Memory Mechanisms of Chern-Simons Context Reservoir Computation

arXiv:2609.13315v1 Announce Type: cross Abstract: We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a

FedLTLib: A Comprehensive Benchmark for Federated Long-Tail Learning

arXiv:2609.15625v1 Announce Type: cross Abstract: Driven by the escalating demand for privacy-preserving computing, Federated Learning (FL) has witnessed remarkable progress, becoming a cornerstone te

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

FFVO: A Feedforward Pose Decoder for Long-Horizon Visual Odometry

model-releasesarxiv-cs-cv

arXiv:2609.13733v1 Announce Type: new Abstract: Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camer

FICAug: Feature-Informed Clustering and Augmentation for Facial-Expression-Based Parkinson's Disease Screening

arXiv:2409.17685v3 Announce Type: replace Abstract: Hypomimia has drawn growing interest as a digital marker for screening Parkinson's disease (PD). However, developing reliable facial-expression-base

Filling the Unseen: Scene Extrapolation via 3D Gaussian Splatting

arXiv:2609.13262v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves photorealistic reconstruction within training view distribution, yet it degrades on out-of-distribution novel views, exhi

researcharxiv-cs-cv

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