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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

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Model Releases

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

DGX agent

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

model-releasesarxiv-cs-cv

22 Sept 2026

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

Industry

We almost let my dad sleep through a stroke. ChatGPT is the reason we didn’t.

I keep replaying that night in my head because we came way too close to doing nothing. We were eating dinner when my dad dropped his chopsticks. He picked them up, dropped them again, then got annoyed

industryr-chatgpt

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

Industry

Web scraping startup Firecrawl closes $75M investment

Firecrawl Inc., a provider of web scraping tools for artificial intelligence agents, today announced that it has raised 75 million in funding. Los Angeles-based venture capital firm Smash Ventures led

industrysiliconangle

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

Applications

We're excited to release the State of Generative Media Report, Volume 2. Generative media has moved from experimentation into production and…

applicationssonya-huang--x

We're excited to release the State of Generative Media Report, Volume 2. Generative media has moved from experimentation into production and that shift looks different across every industry. Built fro

What are Key Factors for Updates in RL for LLM Reasoning?

arXiv:2606.22570v2 Announce Type: replace Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a promising framework for enhancing the reasoning ability of large language mod

safetyarxiv-cs-cl

Local Ai

What are normie reactions to your local AI use like?

There's quite a lot of public anti-AI sentiment at the moment, but a lot of the most common concerns and objections have to do with the politics, economics and ethics of datacenter-based AI. So, when

local-air-localllama

What Can a Recurrent State Safely Forget?

arXiv:2609.23366v1 Announce Type: new Abstract: Recurrent models must preserve information that changes future behavior while suppressing hidden-state error. These objectives conflict: contraction imp

safetyarxiv-cs-lg

What do VLM-Based Vision-Language Navigation Models Rely on: Interpreting and Steering Policy Behavior

arXiv:2609.24576v1 Announce Type: cross Abstract: Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While thi

What Is The Political Content in LLMs' Pre- and Post-Training Data?

arXiv:2509.22367v3 Announce Type: replace Abstract: Large language models (LLMs) reflect politically-slanted opinions in their generated text. Even though it is widely assumed that model behavior stem

What Makes a Good Medical Image Tokenizer? Rethinking Reconstruction and Generation in Medical Image Tokenization

arXiv:2609.24691v1 Announce Type: new Abstract: Latent diffusion models now dominate medical image generation, and every such pipeline rests on a tokenizer that compresses images into the latent codes

What Makes Good Multilingual Reasoning? Disentangling Traces with Measurable Features

arXiv:2604.04720v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) still exhibit large performance gaps between English and other languages, yet much current work assumes these gaps can

Tutorials

What Matters in Designing World Action Models: An Empirical Study

arXiv:2609.24048v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing wor

tutorialsarxiv-cs-ro

Applications

What to expect during Okta’s Oktane event: Join theCUBE Sept. 24

Identity security now determines how safely artificial intelligence agents can access systems and act across enterprise workflows. As AI agents log in to applications and execute tasks, companies must

applicationssiliconangle

What underrated AI tools have actually made you more productive in 2026?

model-releasesr-localllama

I asked this back in 2025, but the AI landscape has changed a lot since then. Not looking for the usual ChatGPT, Claude, Gemini, Midjourney, etc. I'm curious about the lesser-known tools that you actu

Hardware

What’s New for Game Developers: DLSS 5 with 3D-Guided Neural Rendering, NVIDIA ACE Updates, and New RTX Kit Capabilities

NVIDIA’s DLSS 5 introduces a 3D‑Guided Neural Rendering system that adds realistic lighting and material detail to the renderer’s frame while preserving artistic intent; it operates one‑frame‑in/one‑f

hardwarenvidia-developer

When and Why Do Linear Bias Probes Fail? A Geometric and Statistical Theory of Bias Detectability in Large Language Model Representations

arXiv:2609.22337v1 Announce Type: cross Abstract: Linear probing is the standard instrument for detecting social biases in the hidden representations of large language models. Yet reported probe accur

safetyarxiv-cs-lg

When Cosine Similarity Fails to Reflect Linearly Accessible Structure in Dialogue Models

arXiv:2609.22522v1 Announce Type: new Abstract: Cosine similarity is widely used to analyze transformer representations, implicitly assuming that similarity reflects task-relevant structure. We study

Agents

When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving

arXiv:2507.00319v3 Announce Type: replace Abstract: Simulation frameworks have been key enablers for the development and validation of autonomous driving systems. However, existing methods struggle to

agentsarxiv-cs-ro

When Does Adversarial Refinement Help? A Negative Result and Open Problem in Adapting R3GAN to Time Series Imputation

arXiv:2609.23102v1 Announce Type: new Abstract: Diffusion models and transformers have supplanted GANs for multivariate time series imputation, largely on grounds of GAN training instability. R3GAN (N

researcharxiv-cs-lg

When Does Learning Beat Heuristics? A Case Study in Kubernetes Scheduler Score Plugins

model-releasesarxiv-cs-lg

arXiv:2609.22142v1 Announce Type: cross Abstract: Kubernetes scheduler plugins that score candidate nodes are, in production, hand-tuned heuristics. We ask whether a learned scoring function - trained