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UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Models

arXiv:2610.16945v1 Announce Type: new Abstract: Recent advances in multimodal foundation models, exemplified by GPT-6 Astra, raise the prospect of general-purpose embodied reasoning and planning. Usin

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UNISON: A Unified Framework for Learning from Scored Bags

DGX agent

arXiv:2610.15564v1 Announce Type: new Abstract: We introduce UNISON, a unified framework that bridges multiple instance learning and recommendation systems by treating both as instances of learning fr

researcharxiv-cs-lg

14 Oct 2026

Universal Distributed Feature Extraction Complementary to Side Information via H-Score

arXiv:2610.16707v1 Announce Type: cross Abstract: This paper considers a distributed estimation system where edge nodes transmit averaged features to a center node for parameter estimation. A key chal

Tutorials

Universal Incremental Learning: Mitigating Confusion from Inter- and Intra-task Distribution Randomness

arXiv:2503.07035v3 Announce Type: replace Abstract: Existing incremental learning (IL) methods rely on strong assumptions: incoming tasks either introduce exclusively new classes or new domains (i.e.,

tutorialsarxiv-cs-cv

Universal set of Observables for Forecasting Physical Systems through Causal Embedding

arXiv:2105.10759v4 Announce Type: replace-cross Abstract: We show how a pair of points can uniquely represent a left-infinite sequence obtained from observations of an underlying dynamical system thro

researcharxiv-cs-lg

Tutorials

UniW(A)M: A Unified Mixture-of-Experts Framework for World and World-Action Models

arXiv:2610.18697v1 Announce Type: cross Abstract: World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, respectively. Although these mode

tutorialsarxiv-cs-cv

Agents

Unravel: Recovering an Interactive 3D Scene from a Single Image

arXiv:2610.16146v1 Announce Type: new Abstract: We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable a

agentsarxiv-cs-cv

Unrolled Neural Networks for Constrained Optimization

arXiv:2601.17274v2 Announce Type: replace Abstract: We develop unrolled neural networks to solve constrained optimization problems, offering accelerated, learnable counterparts to dual ascent (DA) alg

researcharxiv-cs-lg

UnSAMv2: Self-Supervised Learning Enables Segment Anything at Any Granularity

arXiv:2511.13714v2 Announce Type: replace Abstract: The Segment Anything Model (SAM) family has become a widely adopted vision foundation model, but its ability to control segmentation granularity rem

Unsupervised and Supervised Approaches for Infrared Small Target Detection : Overview, Challenges and Perspectives (Part 2)

arXiv:2610.18291v1 Announce Type: new Abstract: Since the rise of supervised deep learning modelet dets, researchers has attempt to solve infrared small targection using various models like convention

Unsupervised Data Drift Monitoring for Deployed Deepfake Speech Detectors

arXiv:2610.16826v1 Announce Type: cross Abstract: Deepfake speech detectors are typically evaluated as binary classifiers on fixed benchmarks, but deployed systems face evolving attacks, codecs, speak

Unsupervised Domain Adaptation for Cardiac Segmentation: Towards Structure Mutual Information Maximization

arXiv:2204.09334v4 Announce Type: replace-cross Abstract: Unsupervised domain adaptation approaches have recently succeeded in various medical image segmentation tasks. The reported works often tackle

Urbex: Agentic Spatial Grounding for City-Scale 3D Scenes

arXiv:2610.18356v1 Announce Type: new Abstract: City-scale 3D grounding is commonly formulated as candidate ranking, which requires precomputed instance proposals and becomes inefficient in large outd

Tutorials

Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees

arXiv:2610.15049v1 Announce Type: new Abstract: This study aims to evaluate and compare convolutional neural network (CNN) architectures, specifically AlexNet, Inception, LeNet, VGG16, and MobileNet,

tutorialsarxiv-cs-cv

Using Absorbing Markov Chains + EmbeddingGemma 2 as a Decision Engine: ~2ms inference with 100% GTO Parity on Vegas Blackjack

model-releasesr-localllama

[UPDATE / RETRACTION: The '100% GTO' claim had a prompt-leakage bug] We patched the repo to pass strictly neutral states, here are the real, honest numbers: • Latency: Still ~2ms (ONNX + Absorbing Mar

Local Ai

Using Line Segment Tracking to enable ML-based Track Reconstruction in CMS

arXiv:2610.15963v1 Announce Type: cross Abstract: High-pileup conditions in CMS during the HL-LHC era make charged-particle tracking increasingly challenging as detector occupancy and combinatorics gr

local-aiarxiv-cs-lg

Agents

Uvi raises $7.5M to help AI agents learn business context and run at eight times lower cost

Agentic artificial intelligence startup Uvi said today it has raised 7.5 million in seed funding to tackle an expensive problem around business context that’s draining millions of dollars annually fro

agentssiliconangle

Local Ai

v0.40.5

What's Changed mlx: port the Metal custom kernels to CUDA by @dhiltgen in #18657 docs: model recs and language standardization by @anra8571 in #18981 openai: accept custom tool calls in Responses hist

local-aiollama-releases

Value-Preserving Action Quantization

arXiv:2610.17252v1 Announce Type: cross Abstract: Search-based policy learning, such as Monte Carlo tree search (MCTS), offers the flexibility to trade runtime computation for data efficiency and adap

VARI: Robust Text-to-Video Generation via Group-Structured Intent Alignment

arXiv:2610.18189v1 Announce Type: new Abstract: Modern text-to-video (T2V) models generate visually compelling videos, yet meaning-preserving changes in prompt wording can substantially alter semantic

Variable Input Masked Autoencoders for Wrist-Worn Accelerometry

arXiv:2610.17383v1 Announce Type: new Abstract: Large-scale repositories of wearable sensor data have enabled the development of foundation models for human activities and behavior. However, existing

Variance Fingerprints: Component-Wise Identification of Content Factors by Augmentation Design

arXiv:2610.14260v1 Announce Type: new Abstract: Augmentation-based self-supervised learning can recover the content shared across views without separating its underlying factors into individual coordi

Variance-Optimal State Resampling for Reinforcement Learning with Verifiable Rewards

arXiv:2610.15888v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards spends much of its rollout budget on states that yield no learning signal. We recast this as a question a

Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate

arXiv:2610.16578v1 Announce Type: cross Abstract: Modern deep classifiers trained by gradient descent need many passes over the data to become accurate, and even then are not always well calibrated; p

Industry

Vast Data bets stitched-together AI pipelines can’t keep sensitive data in sync

Data sovereignty is becoming an architectural problem as enterprises push artificial intelligence inference toward their most sensitive information. Pipelines assembled from separate tools struggle to

industrysiliconangle

VAttnPO: Visual Attention-Guided Policy Optimization

arXiv:2610.16735v1 Announce Type: new Abstract: Multimodal reinforcement learning with verifiable rewards commonly assigns one sequence advantage to an entire response. This outcome-level signal disti

VbotNav-0: Asynchronous Cloud-Edge Dual-Policy Navigation across Indoor and Outdoor Environments

arXiv:2610.14634v1 Announce Type: new Abstract: Continuous indoor-outdoor navigation connects destination-level reasoning with motion decisions that must respond to current observations. We present Vb

safetyarxiv-cs-ro

Verify, Act, Distill: Turning Test-Time Compute into Test-Time Adaptation for Vision-Language-Action Models

arXiv:2610.14885v1 Announce Type: new Abstract: Test-time compute (TTC), which scores multiple candidate actions at inference time, is a powerful way to improve the execution performance of vision-lan

safetyarxiv-cs-ro

Very cool to see Embedding Gemma 2 by @Google, number on trending on HF! The media and silicon valley bubble only talks about reasoning LLMs…

model-releasesclem-delangue--x

Very cool to see Embedding Gemma 2 by @Google, number on trending on HF! The media and silicon valley bubble only talks about reasoning LLMs when there is a much bigger variety of AI models that are s

VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection

arXiv:2602.16681v2 Announce Type: replace Abstract: Time-series anomaly detection (TSAD) requires identifying both immediate Point Anomalies and long-range Context Anomalies. However, existing foundat

VGGA: Geometry-Grounded Autoencoder for Video Generation

arXiv:2610.16204v1 Announce Type: new Abstract: Autoencoders are the core component of latent video generative models, compressing high-dimensional videos into compact latent spaces for downstream gen

VH-GPO: Verified Handoff for LLM Agent Reinforcement Learning

arXiv:2610.14000v1 Announce Type: new Abstract: Group-relative reinforcement learning methods such as GRPO train large language model (LLM) agents by comparing rollouts for the same task. When every t

Video-Arena: A Scalable Agentic Video Benchmark for Spatiotemporal Capability

arXiv:2610.14158v1 Announce Type: new Abstract: Understanding and tracking a dynamic world are fundamental to visual intelligence. Existing video benchmarks provide limited insight into whether models

Applications

Video-Based Sexual Harassment Detection Using Fine-Tuned Video Transformers

arXiv:2610.15354v1 Announce Type: new Abstract: Sexual harassment represents a pervasive societal challenge, with a substantial proportion of incidents remaining unreported due to insufficient evidenc

applicationsarxiv-cs-cv

VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding

arXiv:2610.15389v1 Announce Type: new Abstract: Video understanding agents rely on a harness to acquire evidence, use tools, and reason, but improving it requires substantial effort. Recent self evolu

VideoJev: System One Model for Video Understanding and Interaction

arXiv:2610.18615v1 Announce Type: new Abstract: Visual agents must turn video observations into timely decisions to track progress and choose what to do next. Building on the emerging System One parad

Agents

VideoSlate: Stateful Commit Control for Temporally Grounded Agentic Video Reasoning

arXiv:2610.16357v1 Announce Type: new Abstract: Agentic video reasoning systems gather and assess video evidence across stages, selecting relevant spans as visual evidence for answering questions. New

agentsarxiv-cs-cv

VIEWCRAFT: Evolving What Multimodal Agents See and How They Read It

arXiv:2610.15915v1 Announce Type: new Abstract: Reusable skills improve multimodal agents without updating model weights, but their effectiveness depends on both the evidence presented and the procedu

Applications

ViewStruct: View-Grounded Articulation and Connectivity Inference

arXiv:2610.16793v1 Announce Type: new Abstract: Interacting with unfamiliar objects requires understanding how their parts connect and move. We introduce ViewStruct, a framework for jointly predicting

applicationsarxiv-cs-cv

VisExMEM: Visual Evidence-Based Explainable Multimodal Evaluation Metric

arXiv:2610.16441v1 Announce Type: new Abstract: Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Explai

Vision Models Capture Complementary Representations in Children That Converge in Adults

arXiv:2610.16860v1 Announce Type: new Abstract: How the relationship between image-text aligned and vision-only models changes across development remains unknown. We applied time-resolved representati

Vision-Predictor-Action: Towards Efficient Embodied AI via Neuro-Symbolic JEPA Predictors

arXiv:2610.15556v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models commonly generate robot actions token by token through Large Language Model (LLM) decoders, causing inference late

Visual Dependence Does Not Imply Answerability: A Systematic Analysis of Answerability Signals in Frozen InstructBLIP

arXiv:2610.17902v1 Announce Type: new Abstract: Visual question answering models often produce plausible responses even when the available visual evidence is insufficient to support a valid answer. Al

Visual Sevoing from Lines

arXiv:2610.18363v1 Announce Type: cross Abstract: In this work, we present a fundamentally new approach to visual servoing using lines. It is based on a theoretical and geometrical study of the main l

Local Ai

Visual Tokens on Demand: Visual Budgeting for Scalable and Efficient Multi-Image Reasoning in Multimodal LLMs

arXiv:2610.18858v1 Announce Type: new Abstract: Multimodal large language models have advanced rapidly, but most remain optimized for single-image inputs. Multi-image reasoning is costly because each

local-aiarxiv-cs-cv

VisualCoding: Learning Executable Skills for Reliable Visual Reasoning

arXiv:2610.14403v1 Announce Type: new Abstract: Learning reusable skills can improve visual reasoning agents, yet applying a skill still requires the agent to implement or invoke a procedure and produ

Visualizing the World Model in an Agent's Value Function

arXiv:2610.14186v1 Announce Type: cross Abstract: Could model-free reinforcement learning algorithms actually be learning a model of the environment? In this work, we apply counterfactual intervention

Visually Legible but Adversarial: Watermark-Constrained Attacks on End-to-End VLMs for Document Understanding

arXiv:2610.15728v1 Announce Type: new Abstract: Visible watermarks convey document ownership, confidentiality, and status, but can also carry adversarial signals. We introduce Auto-Regional Adversaria