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arXiv:2609.01967v1 Announce Type: new Abstract: Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model o

applicationsarxiv-cs-lg

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Applications

Addressing Trust in AI Systems through Education: A Didactic Perspective

DGX agent

arXiv:2609.02453v1 Announce Type: cross Abstract: Machine learning (ML) education faces two persistent and connected obstacles: many educational tools present ML as an opaque black box, which leaves l

applicationsarxiv-cs-ai

3 Sept 2026

Adversarial Stress Testing of Outlier Detection in Subjective Image Quality Assessment

arXiv:2509.06554v2 Announce Type: replace-cross Abstract: In subjective image and video quality assessment, observers rate or compare selected stimuli. Before calculating mean opinion scores (MOSs), u

researcharxiv-cs-lg

Cite or Decline: A Strict Course-Grounded Chatbot for STEM Lecture Videos

model-releasesarxiv-cs-cl

arXiv:2609.01846v1 Announce Type: new Abstract: Recorded lecture videos, often enhanced with search and summarization features, are a standard study resource. However, students cannot easily ask cours

Agents

ClaimReceipt: Verifying Evidence Sufficiency and Coverage in Agent Evaluations

arXiv:2609.01992v1 Announce Type: new Abstract: Agent evaluations face two distinct evidentiary questions: whether a reported claim is recomputable from retained evidence (sufficiency), and whether th

agentsarxiv-cs-ai

Collective creativity in hybrid societies

arXiv:2609.02620v1 Announce Type: new Abstract: Generative AI is changing how cultural artifacts are created and circulated, and with it our understanding of creativity itself. Researchers disagree ab

CoMerge: Conflict-Driven Preference Optimization for Multi-Task Model Merging

model-releasesarxiv-cs-ai

arXiv:2609.02273v1 Announce Type: new Abstract: Model merging provides an efficient paradigm for constructing multi-task large language models (LLMs) without full model retraining, yet it remains chal

Compositional Spectral Prompts for LLM-based Online Time Series Forecasting

arXiv:2609.02093v1 Announce Type: new Abstract: To address the sequential and evolving nature of time series, the Online Time Series Forecasting (OTSF) task has been extensively studied in multiple do

tutorialsarxiv-cs-lg

Deep denoising autoencoder-based non-invasive blood flow detection for arteriovenous fistula

arXiv:2306.06865v2 Announce Type: replace-cross Abstract: Clinical guidelines underscore the importance of regularly monitoring and surveilling arteriovenous fistula (AVF) access in hemodialysis patie

Deep Reinforcement Learning for Reach-Avoid-Stay Problems

arXiv:2410.02898v3 Announce Type: replace-cross Abstract: Reach-Avoid-Stay (RAS) tasks are essential in applications where systems must safely reach a target set and remain within it under all bounded

safetyarxiv-cs-lg

DiffIE: Diffusion-based Open Information Extraction

arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta

Do Large Language Models Always Tell The Same Stories?

arXiv:2606.17350v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet whether these models are capable of gen

Elite political incivility is rising across democracies

arXiv:2503.22411v2 Announce Type: replace Abstract: Is political incivility rising across democracies - and if so, why? Analysing approximately 13.8 million tweets from parliamentarians in 26 countrie

researcharxiv-cs-cl

Enhancing Road Safety Through Multi-Camera Image Segmentation with Post-Encroachment Time Analysis

arXiv:2511.12018v2 Announce Type: replace Abstract: Traffic safety analysis at signalized intersections is essential for reducing vehicle and pedestrian collisions, yet traditional crash-based studies

safetyarxiv-cs-cv

Examining the Vulnerability of Multi-Agent Medical Systems to Human Interventions for Clinical Reasoning

arXiv:2609.02191v1 Announce Type: new Abstract: Human interventions at fault points can alter the diagnostic accuracy of multi-agent medical systems. We defined fault points as moments in AI agent con

safetyarxiv-cs-ai

Exchange Policy Optimization Algorithm for Semi-Infinite Safe Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2511.04147v2 Announce Type: replace Abstract: Safe reinforcement learning (RL) aims to optimize long-term performance while adhering to safety requirements. However, many practical applications

Explainable Information Processing in Particle Swarm Optimization through Landscape and Search Behavior Analysis

model-releasesarxiv-cs-lg

arXiv:2509.06272v5 Announce Type: replace-cross Abstract: Swarm-based optimization algorithms have demonstrated remarkable success in solving complex problems, yet their widespread adoption remains li

Agents

Fetch.ai: An Architecture for Modern Multi-Agent Systems

arXiv:2510.18699v2 Announce Type: replace-cross Abstract: Recent surges in LLM-driven intelligent systems largely overlook decades of foundational multi-agent systems (MAS) research, resulting in fram

agentsarxiv-cs-ai

From topology learning to graph generation: A unifying perspective

arXiv:2609.02286v1 Announce Type: cross Abstract: Learning graph structures from data is a fundamental problem that spans a wide range of signal processing and machine learning tasks. While significan

tutorialsarxiv-cs-lg

Hardware-Accelerated Instance Segmentation for Resource-Constrained Space Robotics with Criticality Analysis

arXiv:2609.02219v1 Announce Type: cross Abstract: Autonomous lunar missions require real-time per- ception under three coupled constraints: extreme low-light conditions, limited onboard compute, and r

safetyarxiv-cs-cv

Hidden-Shot: Towards One-Shot Task Generalization for Low-Level Vision Generalist Models

arXiv:2607.01535v2 Announce Type: replace Abstract: Despite the intense engagement surrounding low-level vision generalist models, their effectiveness in zero/few-shot scenarios beyond learned tasks r

Improved Automatic Target Recognition in Synthetic Aperture Sonar Imagery Using Large Deep Neural Networks

arXiv:2609.01800v1 Announce Type: new Abstract: Automatic Target Recognition (ATR) in Synthetic Aperture Sonar (SAS) is a task largely dominated by deep neural networks (DNNs). Most SAS-ATR models use

InstEditSeg: Instruction-Driven Image Editing for Polyp and Skin Lesion Segmentation

arXiv:2609.02004v1 Announce Type: cross Abstract: Accurate segmentation of polyps and skin lesions is pivotal for clinical diagnosis, yet existing methods struggle with low contrast, ambiguous boundar

Local Ai

Integrated Laser Scanning and Image-Based Topology Optimization Techniques for Detection and Quantification of Visible and Subsurface Structural Defects

arXiv:2609.01808v1 Announce Type: new Abstract: Reliable characterization of structural defects requires methods capable of resolving both directly observable surface damage and damage that is not vis

local-aiarxiv-cs-cv

Kirin: Animal Motion Generation from In-the-Wild Video

arXiv:2609.01823v1 Announce Type: new Abstract: Understanding animal motion is fundamental to modeling animal behavior and biomechanics, yet progress in this area lags far behind human motion research

tutorialsarxiv-cs-cv

Learning the Constitutive Behavior of Materials via Neural Operators and Causal Attention: Case Studies in Plasticity and Damage

arXiv:2609.02194v1 Announce Type: new Abstract: Classical constitutive modeling of path-dependent inelastic materials relies on internal state variables whose evolution equations must be postulated ba

researcharxiv-cs-lg

Applications

Learning to Attract and Repel: Dual Quality Margin Learning for Face Recognition (DQM-Face)

arXiv:2609.02644v1 Announce Type: new Abstract: Face recognition in unconstrained environments remains highly challenging due to diverse and extreme variations encountered in real-world scenarios. To

applicationsarxiv-cs-cv

Learning with Volterra Neural Networks: A System Theoretic Perspective

arXiv:2609.01928v1 Announce Type: new Abstract: Higher-order interaction components are important for signal, image, and video modeling, but explicit high-order operators often suffer from rapidly inc

LLM Watermarking as Big Data Provenance: A Deployment-Oriented Systematization

model-releasesarxiv-cs-cl

arXiv:2607.10103v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become widely deployed, their outputs can be copied, transformed, and redistributed at scale without reliable

Meta-ethics and AI: exploring the novel meta-ethical questions in the era of AI

arXiv:2609.01685v1 Announce Type: new Abstract: With the development of artificial intelligence (AI), the landscape of meta-ethics, which has largely centred on human ethics, faces pressures that may

MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection

arXiv:2609.02493v1 Announce Type: new Abstract: Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locat

researcharxiv-cs-ro

Multimodal Language Models as Text-to-Image Model Evaluators

model-releasesarxiv-cs-ai

arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat

No Data Wasted: A Semi-supervised Generative Model for Incomplete Multi-view Data Integration with Missing Labels

arXiv:2508.11180v2 Announce Type: replace-cross Abstract: Multi-view learning is widely applied to real-life datasets, but it often suffers from both missing views and missing labels. Prior probabilis

tutorialsarxiv-cs-ai

OBJECTION! Lawyer Agents Mitigate Guilty Bias in Legal Judgment Prediction

arXiv:2609.02158v1 Announce Type: cross Abstract: Legal Judgment Prediction (LJP) models are typically trained on documents that describe facts from a prosecutorial perspective. Existing datasets furt

safetyarxiv-cs-ai

Online Non-Monotone DR-Submodular Maximization Matching the Offline 0.401 Factor

arXiv:2609.02145v1 Announce Type: cross Abstract: We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the d-dimensional unit cu

Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising

arXiv:2609.02654v1 Announce Type: new Abstract: Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image stati

tutorialsarxiv-cs-cv

PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation

arXiv:2609.02860v1 Announce Type: new Abstract: Modern crop breeding demands precise organ-level analysis for trait quantification, making plant point cloud segmentation (PPCS) increasingly important.

Progressive Pseudo-Label Optimization for Point-Supervised Change Detection

arXiv:2609.02171v1 Announce Type: new Abstract: Point-supervised change detection (PS-CD) aims to identify pixel-level changes between bi-temporal images using only sparsely annotated points. Although

SHARD: Safe and Helpful Alignment via Self-Reframing Distillation

arXiv:2606.15517v2 Announce Type: replace Abstract: Large language models often struggle with sensitive prompts. They may refuse outright, provide generic safety boilerplate, or fail to address the us

safetyarxiv-cs-cl

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

SlowFast-SCI: Slow-Fast Deep Unfolding Learning for Spectral Compressive Imaging

arXiv:2509.16509v3 Announce Type: replace Abstract: Humans learn in two complementary ways: a slow, cumulative process that builds broad, general knowledge, and a fast, on-the-fly process that capture

tutorialsarxiv-cs-cv

Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension

model-releasesarxiv-cs-lg

arXiv:2407.00966v3 Announce Type: replace Abstract: In traditional models of supervised learning, the goal of a learner-- given examples from an arbitrary joint distribution on R^d imes {pm 1}-- is to

SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models

arXiv:2609.02886v1 Announce Type: new Abstract: We introduce SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference. Training

Agents

SpecMine: A Large-Scale Corpus of Spec-Driven Development Artifacts

arXiv:2608.25202v3 Announce Type: replace-cross Abstract: Spec-Driven Development (SDD) is a fast-emerging practice in which a structured natural-language specification, written by a developer, or (mo

agentsarxiv-cs-ai

Stereo 4D Radar for 3D Object Detection: Integrating Geometric Alignment and Absolute Velocity Estimation

arXiv:2609.02560v1 Announce Type: new Abstract: Four-dimensional (4D) Radar is a powerful sensing modality capable of detecting surrounding three-dimensional (3D) objects under diverse weather conditi

safetyarxiv-cs-cv

TAPVid-MV: A Benchmark for Tracking Any Point in 3D Across Multiple Views

arXiv:2609.01899v1 Announce Type: new Abstract: Multi-camera systems are increasingly practical for robotics, AR/VR, and autonomous driving because complementary views reduce depth ambiguity and prese

Ten Architectures, One Error: Shared Failure Modes in Hyperspectral Classification under Spatially Disjoint Evaluation

arXiv:2609.01786v1 Announce Type: new Abstract: Hyperspectral image classification still relies heavily on random pixel splits within a single scene. The Salinas dataset, randomly split, is among the

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

researcharxiv-cs-lg