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Unison: Harmonizing Motion, Speech, and Sound for Human-Centric Audio-Video Generation

arXiv:2605.08729v1 Announce Type: new Abstract: Motion, speech, and sound effects are fundamental elements of human-centric videos, yet their heterogeneous temporal characteristics make joint generati

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UniUncer: Unified Dynamic Static Uncertainty for End to End Driving

DGX agent

arXiv:2603.07686v2 Announce Type: replace-cross Abstract: End-to-end (E2E) driving has become a cornerstone of both industry deployment and academic research, offering a single learnable pipeline that

local-aiarxiv-cs-cv

12 May 2026

Universal Feature Selection with Noisy Observations and Weak Symmetry Conditions

arXiv:2605.09396v1 Announce Type: cross Abstract: This paper relaxes the restrictive symmetry conditions adopted in [4], [5] and extends their universal feature selection framework to accommodate nois

researcharxiv-cs-lg

Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning

arXiv:2605.08765v1 Announce Type: cross Abstract: Unlearning in large language models (LLMs) aims to remove harmful training data while preserving overall utility. However, we find that existing metho

Applications

Unlocking air traffic flow prediction through microscopic aircraft-state modeling

arXiv:2605.10083v1 Announce Type: new Abstract: Short-term air traffic flow prediction in terminal airspace is essential for proactive air traffic management. Existing approaches predominantly model t

applicationsarxiv-cs-lg

Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why

arXiv:2605.10889v1 Announce Type: cross Abstract: On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this sign

Unpredictability dissociates from structured control in language agents

arXiv:2605.09692v1 Announce Type: new Abstract: Unpredictable behavior is often taken as evidence of control, yet stochastic dispersion and structured action control need not coincide. This paper test

Unsupervised Process Reward Models

arXiv:2605.10158v1 Announce Type: new Abstract: Process Reward Models (PRMs) are a powerful mechanism for steering large language model reasoning by providing fine-grained, step-level supervision. How

safetyarxiv-cs-lg

Unveiling High-Probability Generalization in Decentralized SGD

model-releasesarxiv-cs-lg

arXiv:2605.10205v1 Announce Type: new Abstract: Decentralized stochastic gradient descent (D-SGD) is an efficient method for large-scale distributed learning. Existing generalization studies mainly ad

UPA: Unsupervised Prompt Agent via Tree-Based Search and Selection

arXiv:2601.23273v2 Announce Type: replace Abstract: Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-mak

local-aiarxiv-cs-cl

Upholding Epistemic Agency: A Brouwerian Assertibility Constraint for Responsible AI

arXiv:2603.03971v2 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into hypersuasive, authoritative-seeming verdicts, displacing the justificatory work on which democratic

Urban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception

model-releasesarxiv-cs-cv

arXiv:2605.09936v1 Announce Type: new Abstract: We present Urban-ImageNet, a large-scale multi-modal dataset and evaluation benchmark for urban space perception from user-generated social media imager

Use Case: Invoice processing with local LLM - Which LLM and hardware requirements?

This discussion explores using Ollama to run large language models locally for invoice processing while maintaining control over data. The thread likely addresses selecting appropriate smaller models

local-air-ollama

Useful for Exploration, Risky for Precision: Evaluating AI Tools in Academic Research

arXiv:2605.10125v1 Announce Type: new Abstract: Artificial intelligence (AI) tools are being incorporated into scientific research workflows with the potential to enhance efficiency in tasks such as d

researcharxiv-cs-ai

UserGPT Technical Report

model-releasesarxiv-cs-cl

arXiv:2605.08766v1 Announce Type: cross Abstract: Personalized user understanding from large-scale digital traces remains a fundamental challenge. Traditional user profiling methods rely on discrimina

Users as Annotators: LLM Preference Learning from Comparison Mode

arXiv:2510.13830v2 Announce Type: replace-cross Abstract: Pairwise preference data have played an important role in the alignment of large language models (LLMs). Each sample of such data consists of

UTS at PsyDefDetect: Multi-Agent Councils and Absence-Based Reasoning for Defense Mechanism Classification

arXiv:2605.09769v1 Announce Type: new Abstract: This paper describes our system for classifying psychological defense mechanisms in emotional support dialogues using the Defense Mechanism Rating Scale

UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence

arXiv:2605.09040v1 Announce Type: new Abstract: Modeling ultra-long user sequences involves a difficult trade-off between efficiency and effectiveness. While current paradigms rely on either item-spec

researcharxiv-cs-ai

V-ABS: Action-Observer Driven Beam Search for Dynamic Visual Reasoning

arXiv:2605.10172v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have achieved remarkable success in general perception, yet complex multi-step visual reasoning remains a per

safetyarxiv-cs-cl

v0.30.0-rc15

v0.30.0-rc15 is a release candidate version of Ollama, an open-source platform for running large language models locally. This particular release is part of the development cycle leading toward the st

local-aiollama-releases

V4FinBench: Benchmarking Tabular Foundation Models, LLMs, and Standard Methods on Corporate Bankruptcy Prediction

model-releasesarxiv-cs-lg

arXiv:2605.10896v1 Announce Type: new Abstract: Corporate bankruptcy prediction is a high-stakes financial task characterized by severe class imbalance and multi-horizon forecasting demands. Public da

Applications

VAE with Hyperspherical Coordinates: Improving Anomaly Detection from Hypervolume-Compressed Latent Space

arXiv:2601.18823v3 Announce Type: replace Abstract: Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, one can h

applicationsarxiv-cs-lg

Valid Best-Model Identification for LLM Evaluation via Low-Rank Factorization

model-releasesarxiv-cs-lg

arXiv:2605.10405v1 Announce Type: new Abstract: Selecting the best large language model (LLM) for a fixed benchmark is often expensive, since exhaustive evaluation requires running every model on ever

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations

arXiv:2605.08754v1 Announce Type: new Abstract: Taxiway routing and on-surface conflict avoidance are coupled safety-critical decision problems in airport surface operations. Existing planning and opt

Industry

Vancouver-based quantum computing startup Photonic raised an additional 70M after a 130M raise announced in January, giving it a $2B post-money valuation (Josh Scott/BetaKit)

Josh Scott / BetaKit: Vancouver-based quantum computing startup Photonic raised an additional 70M after a 130M raise announced in January, giving it a 2B post-money valuation — Vancouver-based Photoni

industrytechmeme

Vapi nabs $50M to make voice AI more human

model-releasessiliconangle

Voice artificial intelligence startup Vapi Inc. said today it has raised 50 million in new funding to change the way people talk to computers, experience phone calls and interact with customer support

Variational Inference for Levy Process-Driven SDEs via Neural Tilting

arXiv:2605.10934v1 Announce Type: cross Abstract: Modelling extreme events and heavy-tailed phenomena is central to building reliable predictive systems in domains such as finance, climate science, an

VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models

arXiv:2603.18113v2 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly shape content generation, interaction, and decision-making across the Web, aligning them with hum

Agents

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving

arXiv:2605.08830v1 Announce Type: cross Abstract: End-to-end autonomous driving requires models to understand traffic scenes, infer driving intent, and generate executable motion plans. Recent vision-

agentsarxiv-cs-ai

VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.10485v1 Announce Type: new Abstract: Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominan

Tutorials

VeloGauss: Learning Physically Consistent Gaussian Velocity Fields from Videos

arXiv:2605.10567v1 Announce Type: new Abstract: In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without re

tutorialsarxiv-cs-cv

Verbalized Algorithms: Classical Algorithms are All You Need (Mostly)

arXiv:2509.08150v5 Announce Type: replace Abstract: Reasoning is a fundamentally algorithmic task. Yet current work on LLM-based reasoning relies on free-form generation whose theoretical guarantees (

researcharxiv-cs-cl

VeriContest: A Competitive-Programming Benchmark for Verifiable Code Generation

arXiv:2605.08553v1 Announce Type: cross Abstract: Large language models can generate useful code from natural language, but their outputs come without correctness guarantees. Verifiable code generatio

Verifiable Process Rewards for Agentic Reasoning

arXiv:2605.10325v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has improved the reasoning abilities of large language models (LLMs), but most existing approaches

local-aiarxiv-cs-ai

Verification Mirage: Mapping the Reliability Boundary of Self-Verification in Medical VQA

arXiv:2605.10850v1 Announce Type: new Abstract: Self-verification, re-invoking the same vision language model (VLM) in a fresh context to check its own generated answer, is increasingly used as a defa

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Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward

arXiv:2605.09920v1 Announce Type: cross Abstract: While Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a promising post-training paradigm for Large Language Models (LLMs

VFM-SDM: A vision foundation model-based framework for training-free, marker-free, and calibration-free structural displacement measurement

model-releasesarxiv-cs-cv

arXiv:2605.09677v1 Announce Type: new Abstract: Reliable displacement measurement is fundamental for structural health monitoring and digital engineering workflows, as it provides direct structural re

VidNum-1.4K: A Comprehensive Benchmark for Video-based Numerical Reasoning

model-releasesarxiv-cs-cv

arXiv:2604.03701v2 Announce Type: replace Abstract: Video-based numerical reasoning provides a premier arena for testing whether Vision-Language Models (VLMs) truly 'understand' real-world dynamics, a

Virtual Personas for Language Models via an Anthology of Backstories

arXiv:2407.06576v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained from vast repositories of text authored by millions of distinct authors, reflecting an enormous diver

researcharxiv-cs-ai

VISOR: A Vision-Language Model-based Test Oracle for Testing Robot

model-releasesarxiv-cs-ro

arXiv:2605.10408v1 Announce Type: cross Abstract: Testing robots requires assessing whether they perform their intended tasks correctly, dependably, and with high quality, a challenge known as the tes

Agents

ViSRA: A Video-based Spatial Reasoning Agent for Multi-modal Large Language Models

arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training

agentsarxiv-cs-ai

VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation

model-releasesarxiv-cs-ro

arXiv:2605.08886v1 Announce Type: cross Abstract: Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This

VISTA: A Generative Egocentric Video Framework for Daily Assistance

arXiv:2605.10579v1 Announce Type: new Abstract: Training AI agents to proactively assist humans in daily activities, from routine household tasks to urgent safety situations, requires large-scale visu

safetyarxiv-cs-cl

Visual-ERM: Reward Modeling for Visual Equivalence

arXiv:2603.13224v2 Announce Type: replace-cross Abstract: Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured r

Visual Hand Gesture Recognition with Deep Learning: A Comprehensive Review of Methods, Datasets, Challenges and Future Research Directions

arXiv:2507.04465v4 Announce Type: replace Abstract: The rapid evolution of deep learning (DL) models and the ever-increasing size of available datasets have raised the interest of the research communi

researcharxiv-cs-cv

ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models

arXiv:2510.10606v4 Announce Type: replace Abstract: Post-training Large Vision-and-Language Models (LVLMs) typically involves Supervised Fine-Tuning (SFT) for knowledge injection or Reinforcement Lear

researcharxiv-cs-cv

VLADriver-RAG: Retrieval-Augmented Vision-Language-Action Models for Autonomous Driving

arXiv:2605.08133v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving, yet their reliance on implicit parametric

Vocabulary Hijacking in LVLMs: Unveiling Critical Attention Heads by Excluding Inert Tokens to Mitigate Hallucination

arXiv:2605.10622v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal tasks, yet their reliability is persistently undermined by halluc

local-aiarxiv-cs-cv