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Identity-Centric Video Summarization via Hierarchical Fusion of Biometric, Appearance, and 3D Body Features

arXiv:2609.25837v1 Announce Type: new Abstract: This work presents a video summarization algorithm based on multi-object tracking and person reidentification. We integrate facial embeddings, 3D body-s

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ImIR: Image-Instruction Tuning for All-in-One Image Restoration

DGX agent

arXiv:2609.25267v1 Announce Type: new Abstract: Degradations vary widely across images, so a practical restoration system has to handle many degradation types with one model. A recent and effective re

model-releasesarxiv-cs-cv

23 Sept 2026

Impact Is Not Invalidation: Ask About the Claim, Not the Diff

arXiv:2609.25130v1 Announce Type: new Abstract: Memory systems for coding agents must decide, when a repository changes, which of their stored claims have become false. Content anchoring invalidates a

researcharxiv-cs-cl

Imperfection for Precision: Upcycling Imperfect Data for High-Precision Robotic Manipulation

arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation),

Tutorials

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

tutorialsarxiv-cs-lg

Incorporating LLM Embeddings for Variation Across the Human Genome

arXiv:2509.20702v3 Announce Type: replace-cross Abstract: Recent advances in large language model (LLM) embeddings have enabled powerful representations for biological data, but most applications to d

applicationsarxiv-cs-ai

Incremental Consistency Execution for Autonomous Intelligent Systems

arXiv:2609.24090v1 Announce Type: new Abstract: Long-horizon autonomous intelligent systems rely on heterogeneous components such as large language models, databases, external APIs, and rule engines,

safetyarxiv-cs-ai

Induced Riemannian Metrics for Motion Planning with Constraints

model-releasesarxiv-cs-ro

arXiv:2609.25695v1 Announce Type: new Abstract: In constrained motion planning problems, task and loop-closure constraints restrict a robot's motion to a curved, lower-dimensional submanifold of its c

IndustrialVLA-Bench: A Traceable Multi-Axis Evaluation of Open Robot Policy Models

model-releasesarxiv-cs-ro

arXiv:2609.25562v1 Announce Type: new Abstract: Open robot policies increasingly follow two paradigms: vision-language-action models (VLAs) directly map observations and instructions to actions, where

Information-Theoretic Decoupled Prompt Tuning for Continual Learning

arXiv:2609.26257v1 Announce Type: new Abstract: Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has

safetyarxiv-cs-lg

Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models

arXiv:2609.25927v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning

local-aiarxiv-cs-cl

Initialization and Stopping Tolerance in CPU Dermoscopic Segmentation

arXiv:2609.25685v1 Announce Type: new Abstract: Contour initialization and numerical stopping can jointly affect the evaluation of active-contour segmentation. We examine their interaction using the o

Interpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa

arXiv:2609.25697v1 Announce Type: new Abstract: Purpose: To develop and evaluate an interpretable artificial intelligence (AI) framework for glaucoma screening from low-cost portable, handheld retinal

Interweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models

arXiv:2609.25980v1 Announce Type: new Abstract: Probabilistic time series foundation models (TSFMs) provide coordinate-wise predictive distributions, but these marginals do not determine a joint distr

IntLawNER: A Named Entity Recognition Dataset and Benchmark in International Law

model-releasesarxiv-cs-ai

arXiv:2609.22529v1 Announce Type: new Abstract: International law provides the normative framework through which states coordinate action, regulate armed conflict, and protect human rights, yet its te

ISA-Bench: A Benchmark for Computational Reasoning Across Instruction Set Architectures

model-releasesarxiv-cs-ai

arXiv:2609.22878v1 Announce Type: new Abstract: Large language model code generation benchmarks primarily evaluate well-resourced languages like Python and Java, where models benefit from abundant tra

Isolated Sign Language Recognition for Icelandic Sign Language: Experiments in a Low-resource Setting

arXiv:2609.25862v1 Announce Type: new Abstract: We present the first experiments on isolated sign language recognition (ISLR) for Icelandic Sign Language (ITM). We use ITM SignWiki, a dataset derived

researcharxiv-cs-cl

JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation

arXiv:2609.25322v1 Announce Type: new Abstract: Coordinated bimanual manipulation is challenging because the motion of either arm can alter the shared 3D scene and thereby affect the other arm. Yet mo

JAMPR+/L2D: scalable neural heuristic for constrained vehicle routing problems in dynamic environment

arXiv:2609.26275v1 Announce Type: new Abstract: The vehicle routing problems with real-world constraints (we consider vehicles capacity limits, time windows constrains, pickup-and-delivery multi-depo

Knowledge Pull Requests for Continual Document Authoring

arXiv:2609.26634v1 Announce Type: new Abstract: We introduce Knowledge Pull Requests (KPRs), a framework for continual document authoring that makes each change interpretable. Documents require ongoin

researcharxiv-cs-cl

KwaiMind Technical Report

arXiv:2609.26375v1 Announce Type: new Abstract: Commercial image editing requires product identity preservation, accurate text rendering, and user appeal alongside general editing quality. We present

safetyarxiv-cs-cv

Label-Efficient Learning for Ground-Based Sky-Image Classification: A Benchmark of Transfer Learning, Active Learning, and Pseudo-Labeling on GCD

model-releasesarxiv-cs-lg

arXiv:2609.26631v1 Announce Type: new Abstract: Accurate ground-based cloud classification is important for atmospheric monitoring, solar-energy forecasting, aviation weather assessment, and climate o

LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

safetyarxiv-cs-ai

Ladders of Thought: A Self-Evolving Curriculum of Progressively Simplified Reasoning Traces

arXiv:2609.25643v1 Announce Type: cross Abstract: Large language models (LLMs) excel at reasoning when scaled to hundreds of billions of parameters, but small- and mid-scale models remain brittle reas

Laryngeal Structure Segmentation in High-Speed Videoendoscopy Using Deep Learning

arXiv:2609.26636v1 Announce Type: new Abstract: Laryngeal high-speed videoendoscopy (HSV) offers an effective means of observing the motion of different laryngeal structures along with vibratory behav

applicationsarxiv-cs-cv

Latent Commonality Expectation-Maximisation for Box-supervised Tree Crown Instance Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.26549v1 Announce Type: new Abstract: Individual tree crown segmentation from aerial imagery underpins tree-level carbon accounting, biodiversity, and restoration monitoring at landscape sca

Latent Dataset Distillation for Human Motion Prediction

arXiv:2609.26430v1 Announce Type: new Abstract: Dataset distillation (DD) compresses a large training set into a compact synthetic set while preserving downstream training utility. Although DD has bee

LatentPort: Beyond KV Cache - Cross-Model Transfer of Recurrent Memory in Hybrid Language Models: A 4B-to-9B Hybrid-State Handoff Without Target Prefix Replay

model-releasesarxiv-cs-cl

arXiv:2609.25053v1 Announce Type: new Abstract: Can one language model hand its live memory to another without the receiver rereading the context? We demonstrate useful persistent hybrid-state transfe

Latest Exact Match Attention

arXiv:2609.25802v1 Announce Type: cross Abstract: We introduce latest exact match attention (LEMA), an attention variant for transformers where queries and keys are binarized and each query attends on

local-aiarxiv-cs-cl

Layout-Guided Masking for GROBID: Lightweight Structural Gains in Large-Scale Scientific PDF Ingestion

model-releasesarxiv-cs-cl

arXiv:2609.26381v1 Announce Type: new Abstract: Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems. Recent vision-based parsers improve

Agents

LazyAgent: Demand-Driven Materialization and Physical Optimization of Agentic Programs

arXiv:2609.23058v1 Announce Type: new Abstract: Current agent runtimes that plan before acting generally execute a step once it becomes ready. We present LazyAgent, a unified execution framework for a

agentsarxiv-cs-ai

Leaky-integrator reconstruction: taming error accumulation in recursive differenced time-series forecasting

arXiv:2609.23378v1 Announce Type: new Abstract: We introduce leaky-integrator reconstruction, a training-free method that cures the error accumulation of recursive differenced forecasting. Our first c

researcharxiv-cs-ai

LEAP-NBV: Lightweight Edge Active-Perception for Foundation-Model Next-Best-View Planning

model-releasesarxiv-cs-ai

arXiv:2609.23974v1 Announce Type: new Abstract: Foundation models are endowing autonomous systems with greater intelligence, enabling a more comprehensive understanding of the environment through visu

Learnable Classifier-Free Guidance Null Embeddings for Enhanced Controllable Speech Synthesis

arXiv:2609.25411v1 Announce Type: cross Abstract: Classifier-free Guidance (CFG) is widely adopted in text-to-speech (TTS) systems to enhance generation quality and conditioning fidelity by interpolat

Learning 3D biophysical cell properties from 2D images and cell-population statistics

arXiv:2609.22410v1 Announce Type: new Abstract: Inferring 3D cellular properties from 2D microscopy is difficult when a reference instrument reports only population statistics rather than labels for i

local-aiarxiv-cs-ai

Learning Air-Ground Motion Control with Temporal Mode Switching and Cross-Terrain Tracking

arXiv:2609.26564v1 Announce Type: new Abstract: Passive-wheeled terrestrial-aerial bimodal vehicles (TABVs) combine aerial mobility with energy-efficient ground locomotion. However, reliable air-groun

Learning Defensive Policies against Diverse Inference Attacks for Smart Meter Privacy

arXiv:2609.25484v1 Announce Type: new Abstract: Smart meter (SM) data provides fine-grained visibility into household energy consumption, but also exposes users to privacy risks. Inference attacks, kn

Learning Diagnostic Reasoning for Decision Support in Toxicology

arXiv:2603.29608v2 Announce Type: replace Abstract: Acute poly-substance intoxication requires rapid, life-saving decisions under substantial uncertainty, as clinicians must rely on incomplete ingesti

safetyarxiv-cs-cl

Learning from Humans for Proactive Assistance in Human-Robot Collaborative Transport

arXiv:2609.25351v1 Announce Type: cross Abstract: We focus on human-robot collaborative transport, a challenging task of broad relevance spanning logistics, manufacturing, and the home, in which a use

Learning Neural Feedback Linearization for Data-driven Systems via Augmented Lagrangian

arXiv:2609.25163v1 Announce Type: new Abstract: The paper proposes a novel data-driven framework for designing and training a feedback linearizing controller by explicitly incorporating relative degre

Learning to bin: differentiable and Bayesian optimization for multi-dimensional discriminants in high-energy physics

model-releasesarxiv-cs-lg

arXiv:2601.07756v2 Announce Type: replace-cross Abstract: Categorizing events using discriminant observables is central to many high-energy physics analyses. Yet, bin boundaries are often chosen manua

Learning to Defer with Guidance on Real World Medical Data

arXiv:2609.26384v1 Announce Type: new Abstract: Medical image interpretation is high-volume and time-consuming, and while AI interpretation can reduce workload, fully autonomous deployment carries pot

safetyarxiv-cs-lg

Learning to Fluctuate: Statistical Foundations for Causal Tabular Pretraining

model-releasesarxiv-cs-lg

arXiv:2609.26290v1 Announce Type: cross Abstract: Causal tabular foundation models amortize effect estimation across synthetic mechanisms, but latent-effect supervision rewards posterior shrinkage ins

Learning to Plan in Human-Robot Collaboration: Multimodal Reinforcement Learning for Adaptive Interaction

arXiv:2609.25274v1 Announce Type: new Abstract: Robot assistants for older adults and people with disabilities need to perform collaborative tasks with users effectively. The core component of these s

Learning Urban Access Costs from Origin-Destination Flows via Inverse Optimal Transport

arXiv:2606.14157v2 Announce Type: replace Abstract: Cities deliver basic services through mixed public-private facility networks, including schools, clinics, transit providers, and subsidized service

Tutorials

Less Is More in the Long Tail: Stage-Adaptive Sample Selection for Annotation-Efficient Dense Prediction

arXiv:2609.25850v1 Announce Type: new Abstract: Deep learning performance generally improves with increasing training data, yet this scaling is fundamentally constrained by annotation cost in large-sc

tutorialsarxiv-cs-cv

Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping

arXiv:2609.26325v1 Announce Type: cross Abstract: Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on acc

local-aiarxiv-cs-ro

LiDAS: Lighting-driven Dynamic Active Sensing for Nighttime Perception

arXiv:2512.08912v2 Announce Type: replace-cross Abstract: Nighttime environments pose significant challenges for camera-based perception, as existing methods passively rely on the scene lighting. We i

applicationsarxiv-cs-ro