All entries

Two-Point Local Optimality in k-Means via Boundary-Point Screening

arXiv:2610.06182v1 Announce Type: new Abstract: Lloyd's algorithm and the discrete local (D-local) optimization method (Li et al., 2025) for k-means provide only weak local-optimality guarantees, and

Two-Sample Testing via Path-based Inference

Content type

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DGX agent

arXiv:2610.05684v1 Announce Type: cross Abstract: Modern deep generative models are primarily studied for their ability to generate realistic samples, yet the generative dynamics they learn can also s

model-releasesarxiv-cs-lg

6 Oct 2026

ufakzeka-karar: An Open Turkish Typed-Decision Model with Order-Invariant Option Scoring

arXiv:2610.06744v1 Announce Type: cross Abstract: ufakzeka-karar is an open Turkish decision model with 182,494,466 parameters. Given a Turkish text and questions of a fixed answer type (a choice, a l

UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance

arXiv:2610.05932v1 Announce Type: new Abstract: Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditionin

Tutorials

Ultrasound Operator Guidance Using World Modeling and Retrieval Based Action Planning

arXiv:2610.06008v1 Announce Type: cross Abstract: Ultrasound is widely used, but acquisition quality is heavily dependent on the operator's knowledge and expertise. With demand for examinations outpac

tutorialsarxiv-cs-cv

UnAct: Gradient-Free Unlearning via Targeted Activation Intervention

arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method

Underscoring the Problem: Why Softpick Fails at Initialization

arXiv:2610.05488v1 Announce Type: new Abstract: Softmax attention gives every token a nonzero weight, which in trained models concentrates into attention sinks and massive activations that widen the d

Understanding Certified Training with Interval Bound Propagation

arXiv:2306.10426v3 Announce Type: replace Abstract: As robustness verification methods are becoming more precise, training certifiably robust neural networks is becoming ever more relevant. To this en

Understanding Clustering in Slot Attention via Particle Dynamics

arXiv:2610.04493v1 Announce Type: cross Abstract: Studying attention through the lens of interacting particle dynamics has shown how token clustering can emerge from the underlying dynamics. We extend

Understanding Gap-Dependent Regret for Optimism-Based Reinforcement Learning with Linear Function Approximation

arXiv:2602.20297v2 Announce Type: replace-cross Abstract: We study gap-dependent regret for reinforcement learning with linear function approximation. While prior works have established gap-dependent

Understanding over-squashing and bottlenecks on graphs via curvature

arXiv:2111.14522v4 Announce Type: replace-cross Abstract: Most graph neural networks (GNNs) use the message passing paradigm, in which node features are propagated on the input graph. Recent works poi

Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization

arXiv:2610.05329v1 Announce Type: new Abstract: Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). R

UniBRep: Learning Unified Geometry and Topology for Image-conditioned B-Rep Generation

arXiv:2610.04092v1 Announce Type: new Abstract: Generating a boundary representation (B-rep) conditioned on a single image requires faithful reconstruction of geometry, valid topology, and support for

Uniform-in-time convergence bounds for Persistent Contrastive Divergence algorithms

arXiv:2510.01944v2 Announce Type: replace-cross Abstract: We propose a continuous-time formulation of a noisy persistent contrastive divergence (PCD)-like method for maximum likelihood estimation (MLE

Agents

UniFunc3D: Unified Active Spatial-Temporal Grounding for 3D Affordance Segmentation

arXiv:2603.23478v2 Announce Type: replace Abstract: Affordance segmentation in 3D scenes requires an agent to ground implicit natural-language instructions into precise masks of fine-grained interacti

agentsarxiv-cs-cv

UniSlider: Perceptually Uniform Sliders for Continuous Image Editing

arXiv:2610.06831v1 Announce Type: new Abstract: Sliders provide an intuitive interface for continuous image editing. In current generative approaches, however, the slider is simply a rescaling of the

Universal Test-Time Training

arXiv:2610.05484v1 Announce Type: cross Abstract: Recent Test-Time Training (TTT) architectures compress context into fast weights that are updated online and queried as memory. Existing TTT designs k

Universality and Convergence of Generative Flows

arXiv:2610.05490v1 Announce Type: new Abstract: Generative flows sample from an unnormalized target by training a flow to be balanced, and the training loss is the signal a practitioner watches. We as

safetyarxiv-cs-lg

Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

arXiv:2610.05425v1 Announce Type: new Abstract: Automated checks of radiology reports may rely on AI-generated checklists that leave findings unmentioned. We used reinforcement learning to train a vis

unsloth/Qwen3.8-Flash-Next-GGUF is being updated

model-releasesr-localllama

Looks like Unsloth is updating https://huggingface.co/unsloth/Qwen3.8-Flash-Next-GGUF to work with llama.cpp, so hopefully this will resolve the issue of having two different GGUF versions of Qwen Fla

Applications

Usefulness of Quantile-Aware Diffusion Modeling for Highly Imbalanced Tabular Data

arXiv:2610.05825v1 Announce Type: new Abstract: Classification problem in the context of highly imbalanced data is a major challenge in many real-world applications (e.g., FinTech, healthcare, etc.).

applicationsarxiv-cs-lg

Industry

Utah gives startup Nolla Health permission to start issuing AI automated prescriptions for acne treatments

Utah has become the first state in the U.S. to give an artificial intelligence startup permission to automate the approval of prescription refills with only minimal oversight from human physicians. In

industrysiliconangle

Local Ai

v0.40.0-rc6: model: add multimodal embeddings (#18820)

Implements the EmbeddingGemma2Model architecture on the MLX runner: 24-layer bidirectional text encoder with PLE, shared gemma4 vision/audio towers, mean-pool + L2 output. /api/embed accepts per-item

local-aiollama-releases

Valid Stopping in Adaptive Generator-Verifier Loops

arXiv:2610.06432v1 Announce Type: cross Abstract: Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow ter

VAMPS: Visual and Motor Policies from Sampling-Based Planning

arXiv:2610.05331v1 Announce Type: cross Abstract: Learning robot policies directly on physical systems remains difficult because data collection is costly and policy exploration can be unsafe. We intr

safetyarxiv-cs-lg

Variance-Aware Fine-Grained Gap-Dependent Bounds for Online Reinforcement Learning

arXiv:2610.04752v1 Announce Type: cross Abstract: We study model-free online reinforcement learning (RL) for episodic tabular Markov decision processes, focusing on both gap-dependent regret and polic

safetyarxiv-cs-lg

Tutorials

Variance-Optimal Control Variates for Learning with Black-box Feedback

arXiv:2610.04766v1 Announce Type: new Abstract: Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposi

tutorialsarxiv-cs-lg

Tutorials

Variational Quantum Attention for Molecular Graph Learning

arXiv:2610.04588v1 Announce Type: cross Abstract: Molecular property prediction is central to computational drug discovery, where graph neural networks learn to weight neighboring atomic environments

tutorialsarxiv-cs-lg

Agents

Vast uses tiered storage to ease AI agent memory demands

AI agent memory is creating new demands on infrastructure as agents run longer sessions and spread across the enterprise. Retaining that context and making it available when needed puts pressure on me

agentssiliconangle

VCURF: Virtual Camera-based Uncertainty of Radiance Fields

arXiv:2610.04076v1 Announce Type: new Abstract: Radiance fields, implemented with either implicit (NeRF) or explicit (Gaussian Splatting) representations, are advancing the state of the art in novel v

Local Ai

Vela: Scaling Vision-Language-Action Models with Adaptive Action Curve Parametrization

arXiv:2610.05230v1 Announce Type: new Abstract: Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed outp

local-aiarxiv-cs-ro

Agents

VepAgent: Bridging Causal-Transition via Tool-Augmented Reinforcement Learning for Video Event Prediction

arXiv:2610.06293v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in video understanding, yet their reliance on retrospective summarizatio

agentsarxiv-cs-cv

VERA: Verdict-Conditioned Reliability for Adaptive LLM Judges

arXiv:2610.05452v1 Announce Type: new Abstract: Accurately estimating judgment reliability is a central challenge in adapting LLM judges to newly verified feedback while preserving previously learned

Local Ai

Verifier-Guided Synthetic Augmentation for 3D Human Shape Generation

arXiv:2610.04006v1 Announce Type: new Abstract: Limited training data diversity constrains generative modeling of 3D human bodies: conservative models remain close to observed examples, whereas explor

local-aiarxiv-cs-cv

VGGT-Bridge: Beyond Sequential Pose Graphs via Coarse-Stride Skip Edges

arXiv:2610.06594v1 Announce Type: new Abstract: Feed-forward visual geometry transformers such as VGGT reconstruct dense 3D structure from images in a single forward pass, simplifying multi-view 3D re

safetyarxiv-cs-cv

VICON: Visual-Inertial-Contact based Hand-Object Tracking for Manipulation Datasets

arXiv:2610.05180v1 Announce Type: new Abstract: Learning dexterous manipulation benefits from human demonstration datasets that capture diverse and natural hand-object interactions. In particular, con

researcharxiv-cs-ro

Video Encoders Built on Image Representations

arXiv:2610.06616v1 Announce Type: new Abstract: The design of a video encoder determines when frames begin to interact and which frame-specific visual evidence remains accessible to the language model

Applications

Video Replanning via Latent Embedding Refinement and Rejection-Based Sampling

arXiv:2510.17315v3 Announce Type: replace Abstract: Video planning has emerged as a flexible framework for robot manipulation, in which a generative model predicts a video of task completion, and a do

applicationsarxiv-cs-ro

Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos

arXiv:2610.04432v1 Announce Type: new Abstract: Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manu

VideoResearchAgent: Grounded Task Synthesis and Sim-to-Real RL for Open-Web Video Research

arXiv:2610.04911v1 Announce Type: cross Abstract: Existing deep research agents are designed primarily for text- and image-based web sources, while video reasoning systems typically assume that releva

VideoTapestry: Query-Adaptive Memory Refinement for Multi-Agent Long-Video Understanding

arXiv:2610.06672v1 Announce Type: new Abstract: Long-video understanding places substantial demands on memory, as answering questions often requires retrieving information distributed across extended

Applications

Virtual model control for compliant reaching under uncertainties

arXiv:2610.05695v1 Announce Type: new Abstract: Virtual Model Control (VMC) is an approach to design a controller for force-controlled robots in complex uncertain environments. While this method was p

applicationsarxiv-cs-ro

Vision-enabled detection of safety helmet compliance in construction zones

arXiv:2610.05756v1 Announce Type: new Abstract: In the rapidly evolving field of construction management, worker safety remains a top priority. This paper introduces an innovative vision-based system

safetyarxiv-cs-cv

Hardware

Vision Transformer Ensembles for Panoramic Street Segmentation

arXiv:2610.06063v1 Announce Type: new Abstract: Semantic segmentation of street panoramas can support detailed descriptions of urban environments, yet small datasets and unequal training costs make mo

hardwarearxiv-cs-cv

Visual Grounding Safety in Vision-Language Models

arXiv:2610.05637v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly trained to generate structured outputs like points and bounding boxes that downstream interfaces, agent

safetyarxiv-cs-cv

Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design

arXiv:2610.06400v1 Announce Type: new Abstract: Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, such as those encountered in sear

safetyarxiv-cs-ro

VisualErase: Dual-Branch Visual Trajectory Redirection for Robust Concept Erasure in Text-to-Image Diffusion Models

arXiv:2610.05000v1 Announce Type: new Abstract: Concept erasure is essential for the safe deployment of text-to-image diffusion models, as they may reproduce harmful, copyrighted, or privacy-sensitive

VLA-ZO: Fast Zeroth-Order Adaptation for Vision-Language-Action Models

arXiv:2610.06271v1 Announce Type: new Abstract: Adapting vision-language-action (VLA) models to deployment-time distribution shifts is important for reliable robotic operation, but conventional first-

researcharxiv-cs-ro