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arXiv:2609.23169v1 Announce Type: new Abstract: High-quality texture generation is essential for creating realistic and production-ready 3D assets. Recent multi-view diffusion methods have shown promi

applicationsarxiv-cs-cv

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Human DGX agent

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Uncertainty and Business-Aware Remaining Useful Life Estimation for Semiconductor Manufacturing

DGX agent

arXiv:2609.22160v1 Announce Type: new Abstract: Semiconductor manufacturing relies on tightly interconnected components, so early identification of the assets most likely to fail is essential to preve

applicationsarxiv-cs-lg

22 Sept 2026

Applications

Uncertainty-Weighted Fusion of Image and Synthetic Event for Video Anomaly Detection

arXiv:2505.02393v3 Announce Type: replace Abstract: Most existing video anomaly detectors rely on RGB frames alone, which limit their ability to capture abrupt or transient motion cues that are critic

applicationsarxiv-cs-cv

Unified Learning of Temporal Task Structure and Action Timing for Bimanual Robot Manipulation

arXiv:2603.06538v2 Announce Type: replace Abstract: Bimanual manipulation requires both temporal task structure - which actions precede or overlap others - and concrete timing - when each action start

researcharxiv-cs-ro

Local Ai

UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations

arXiv:2609.22217v1 Announce Type: new Abstract: Global In-situ Observation (GIO) provides fine-scale, direct records of the global weather system from sparse point stations, making it an indispensable

local-aiarxiv-cs-lg

UniK: Universal Knowledge Perception for Digital and Physical AI

arXiv:2609.23971v1 Announce Type: cross Abstract: Two transformative classes of AI systems are reshaping how organizations operate: extit{digital AI}, which reasons over enterprise knowledge to power

UniPoint: Unified Point-Level Sensor Fusion for Humanoid Locomotion Across Challenging Terrains

arXiv:2609.23666v1 Announce Type: new Abstract: Open-world deployment requires humanoid robots to cross highly heterogeneous terrain safely, with perception that simultaneously provides wide coverage,

Applications

Universal Multi-Modal Traceformer: Integrating Heterogeneous Context for Process Event Prediction

arXiv:2609.24579v1 Announce Type: new Abstract: Event logs arise in a wide range of real-world processes, capturing not only event activities and timestamps but also multi-modal contextual information

applicationsarxiv-cs-lg

Agents

Universal Observatory Graphs for Distributed Sky Coverage and Artificial Intelligence Based Interplanetary Routing

arXiv:2609.22244v1 Announce Type: new Abstract: This research proposes the Universal Observatory Graph (UOG), an AI-driven framework for distributed astronomical observation across the Solar System. T

agentsarxiv-cs-lg

Unlocking Pretrained Vision Transformers for Time Series Classification

arXiv:2506.08641v3 Announce Type: replace-cross Abstract: Adapting vision models for time series analysis is compelling, yet all existing approaches are falling short of dedicated time series foundati

Local Ai

Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior

arXiv:2609.24265v1 Announce Type: cross Abstract: Unsupervised anomaly detection (UAD) aims to localize abnormal regions in medical scans without pixel-level annotations. A typical strategy seeks to r

local-aiarxiv-cs-cv

URA-NER: A Unified Retrieval-Augmented Framework with Retrieval Alignment and Uncertainty Reduction for Low-Resource NER

arXiv:2609.24372v1 Announce Type: new Abstract: In-context learning (ICL) based on large language models (LLMs) has shown promising potential in alleviating performance bottlenecks caused by the limit

Uranus: Building the Next-Generation Simulation Infrastructure for Embodied AI

arXiv:2609.24815v1 Announce Type: new Abstract: Scalable simulation is essential for robot data generation, policy training, evaluation, and safe iteration, yet real-world interaction is costly and co

Used, Mentioned, or Condemned? A Controlled Contrast-Set Diagnostic for the Use-Mention Distinction in Code-Mixed Hinglish Misogyny Detection

arXiv:2609.22261v1 Announce Type: new Abstract: Lexicon-driven misogyny detectors cannot, by construction, distinguish a slur used against a woman from the same slur mentioned in counter-speech ('don'

User-Level Handover Decision Making Based on Machine Learning Approaches

arXiv:2609.22593v1 Announce Type: new Abstract: This letter covers a broad comparison of methods for classification and regression applications for a user-level handover decision making in scenarios w

researcharxiv-cs-lg

Using Composition Operators to Linearize LLM Semantic Transformations

arXiv:2609.22143v1 Announce Type: new Abstract: Machine learning learns functions: prompt to response, image to caption. What these functions are mathematically remains hard to say. We present a metho

Validating, Not Sampling: Region-Level Robustness of Vision-Language and Vision-Language-Action Models

arXiv:2609.22293v1 Announce Type: new Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) are increasingly deployed in real-world applications. There, a small perturbation

ValueDiff: Value-Geometric KV Cache Eviction for Sink-Suppressed LLMs

arXiv:2609.23314v1 Announce Type: new Abstract: Modern LLMs with QK-normalization, gated attention, learned attention sinks, or logit softcapping exhibit weaker persistent attention sinks, on which ex

researcharxiv-cs-lg

Agents

VDGS: Visibility-Driven Large-Scale 3D Gaussian Splatting for Aerial Scene Reconstruction

arXiv:2609.23049v1 Announce Type: new Abstract: Large-scale scene reconstruction is a critical foundational technology in robotic autonomous systems such as 3D mapping and autonomous driving. In recen

agentsarxiv-cs-cv

Verti-WM: A Physics-Aided Exteroceptive World Model for Off-Road Reinforcement Learning

arXiv:2609.23118v1 Announce Type: new Abstract: Reinforcement learning for off-road navigation requires extensive vehicle-terrain interaction data, which are costly to collect in high-fidelity simulat

VGG16-MCA UNet: Whole-Tumor Segmentation in 2D FLAIR MRI with Decoder-Side Channel Attention

arXiv:2609.23919v1 Announce Type: cross Abstract: Automated brain tumor segmentation supports diagnosis, treatment planning, and monitoring of disease progression, but building models that generalize

VGGT-Prime: Compute-Adaptive Mixture-of-Heads for Efficient Visual Geometry Transformers

arXiv:2609.23733v1 Announce Type: new Abstract: Feed-forward visual geometry models such as the Visual Geometry Grounded Transformer (VGGT) have recently enabled direct 3D reconstruction from multi-vi

VibeMemBench: Evaluating Memory Systems for Coding Agents on Real Repository Coding Tasks

arXiv:2609.23570v1 Announce Type: cross Abstract: Coding agents operate on real repository coding tasks, and persistent memory systems promise to reuse experience across tasks. Yet existing evaluation

Video-based Surgical Skill Assessment Using Dynamics-and-Uncertainty-Aware Tree-based Gaussian Process Classifier

arXiv:2609.24619v1 Announce Type: new Abstract: The proposed pipeline integrates a representation-flow convolutional neural network with a dynamics- and uncertainty-aware tree-based Gaussian Process c

Video-STLayout Pre-training

arXiv:2609.24031v1 Announce Type: new Abstract: In recent years, pre-training has become fundamental to learning effective video representations, enabling strong transfer to downstream tasks. A popula

VideoGen-Agent: Reinforcing Video Generation Agents

arXiv:2609.24997v1 Announce Type: new Abstract: Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to sat

Vimarsha: Faithful ASR Evaluation for Indian Languages with Demographic Diversity, In-the-Wild Audio and Spelling Variations

arXiv:2609.24199v1 Announce Type: new Abstract: Evaluation benchmarks for Indian language automatic speech recognition (ASR) suffer from two systematic biases: optimistic scores from clean, controlled

Virtual neural networks: hundreds of souls in a body

arXiv:2609.24782v1 Announce Type: new Abstract: A new concept, termed virtual neural networks, is introduced, where the count of trainable parameters is kept constant, and scalability is attained pure

Vision Transformers versus convolutional neural networks for fine-grained orchid genus identification in a species-rich, data-poor flora: a controlled benchmark on the Orchidaceae of New Guinea

arXiv:2609.24064v1 Announce Type: new Abstract: New Guinea is the world's richest island flora (~2,856 orchid species), yet most species are represented by only a handful of photographs, far fewer tha

Local Ai

Vision-Wireless Fusion for Multi-User Localization: A Cross-Modal Transformer Approach

arXiv:2609.23372v1 Announce Type: new Abstract: Accurate multi-user localization is challenging in complex urban environments, where wireless measurements can become ambiguous under noise, blockage, a

local-aiarxiv-cs-cv

Vision2CAD: A Visual Agent Harness for Explicit Geometry Referencing and Localization in Parametric CAD Modeling

arXiv:2609.22688v1 Announce Type: new Abstract: Generating parametric CAD models requires accurate geometry and stable feature dependencies. Existing methods face challenges in selecting geometric ref

Agents

VISTA: An Attention-Based Multi-Agent Reinforcement Learning Architecture for Space Situational Awareness Sensor Tasking

arXiv:2609.23875v1 Announce Type: new Abstract: The rapid growth of resident space objects is increasing the complexity of space situational awareness sensor tasking, challenging classical optimizatio

agentsarxiv-cs-lg

VISTA: Video-Injected Stylized Text-to-Animation

arXiv:2609.23817v1 Announce Type: new Abstract: We present VISTA, a two-stage framework for generating stylized 3D human motion by fusing structural content from text prompts with expressive style fro

Visual Graph Reasoning via Knowledge Compilation

arXiv:2609.22327v1 Announce Type: cross Abstract: Visual graph reasoning requires answering graph-theoretic questions directly from graph images, where graph topology and state are conveyed visually r

Visuomotor Robotic Pruning in Planar Orchards Using Hybrid Reinforcement Learning

arXiv:2609.24906v1 Announce Type: new Abstract: Dormant tree pruning is labor-intensive yet essential for maintaining modern high-productivity fruit orchards. In this work, we focus on pruning of mode

Tutorials

VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos

arXiv:2510.24904v2 Announce Type: replace Abstract: Although recent video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camer

tutorialsarxiv-cs-cv

vla.simd: Efficient CPU Inference for Language-Conditioned Manipulation

arXiv:2609.24274v1 Announce Type: new Abstract: Deploying language-conditioned manipulation without a dedicated GPU requires efficient inference and action chunks that cover the delay between policy q

VLPSA: Vision-Language-Poisson-Safe Actions for Full-Body Safety of Learned Policies

arXiv:2609.22462v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable increasingly general-purpose robotic manipulation, but such learned policies do not provide safety guarantees

VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder

arXiv:2307.00852v3 Announce Type: replace Abstract: The natural language generation domain has witnessed great success thanks to Transformer models. Although they have achieved state-of-the-art genera

Vox-Infinity: Benchmarking the Limits of Long-Context Spoken Language Models

arXiv:2609.22452v1 Announce Type: new Abstract: Long-context understanding remains a fundamental challenge for large language models, as excessively long inputs often lead models to forget salient inf

VPRune: Efficient Training-free Pre-LLM Visual Token Pruning

arXiv:2609.24485v1 Announce Type: new Abstract: Visual token pruning is a promising approach to reducing the inference cost of large vision-language models (LVLMs), yet aggressive token reduction ofte

VRWKV-Editor: Reducing quadratic complexity in transformer-based video editing

arXiv:2509.25998v4 Announce Type: replace Abstract: In light of recent progress in video editing, deep learning models focusing on both spatial and temporal dependencies have emerged as the primary me

VT-Bridge: Bridging Pretrained Foundation VLAs to VTLAs via Lightweight Residual Adaptation

model-releasesarxiv-cs-ro

arXiv:2609.22606v1 Announce Type: new Abstract: Vision-Tactile-Language-Action (VTLA) models have demonstrated clear advantages over Vision-Language-Action (VLA) models in contact-rich manipulation. H

Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation

arXiv:2606.18389v2 Announce Type: replace Abstract: Large language models (LLMs) have become an effective tool for synthetic data generation, including for low-resource languages, where generated data

Watching Quantum Models Think: Hilbert-Space Interpretability in Quantum Transformer Blocks

arXiv:2609.23016v1 Announce Type: cross Abstract: Deep learning models are powerful but opaque. As quantum machine learning matures, the field faces a defining choice: build quantum models that are eq

researcharxiv-cs-lg

WaveFront Decoding: Parallelized Self-Speculative Decoding for Looped Language Models

model-releasesarxiv-cs-lg

arXiv:2609.23033v1 Announce Type: new Abstract: Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequen

Weak Ties, Strong Signals: Efficient Training Data Detection in Diffusion LLMs via Independent Token Sampling

arXiv:2609.22145v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a compelling alternative to autoregressive models, yet they may expose sensitive training data during de

WebMRIQC: A Web-Based Implementation of MRIQC for Accessible MRI Image Quality Assessment in Resource-Constrained Settings

arXiv:2609.24014v1 Announce Type: new Abstract: Reliable quality control (QC) of magnetic resonance imaging (MRI) is essential for reliable diagnostic neuroimaging, yet standard manual assessment is s