All entries

Ultraconstructive Model Theory via Bounded Adversarial Finite Structures

arXiv:2608.07534v1 Announce Type: cross Abstract: Ultraconstructive Model Theory (UCMT) replaces idealized satisfaction, at finite compu- tational scale, by bounded adversarial survival. A finite part

applicationsarxiv-cs-ai

Unaccountable Delegation, Fading Skills: Mapping the Risks of Workplace AI Agents

DGX agent

arXiv:2608.08601v1 Announce Type: new Abstract: To anticipate socio-technical risks from AI agents, organizations need taxonomies to classify them. However, existing AI risk taxonomies focus on broad

safetyarxiv-cs-ai

11 Aug 2026

Uncertainty-Aware 4D Gaussian Splatting for Monocular Occluded Human Rendering

arXiv:2602.06343v3 Announce Type: replace Abstract: High-fidelity rendering of dynamic humans from monocular videos typically degrades catastrophically under occlusions. Existing solutions incorporate

Uncertainty-Aware Variational Reward Factorization via Probabilistic Preference Bases for LLM Personalization

arXiv:2604.00997v2 Announce Type: replace Abstract: Reward factorization personalizes large language models (LLMs) by decomposing rewards into shared basis functions and user-specific weights. Yet, ex

safetyarxiv-cs-cl

Understanding Alternating Minimization for Matrix Completion

arXiv:1312.0925v4 Announce Type: replace Abstract: Alternating Minimization is a widely used and empirically successful heuristic for matrix completion and related low-rank optimization problems. Theo

researcharxiv-cs-lg

Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs

arXiv:2608.08506v1 Announce Type: new Abstract: Training-free low-rank compression frameworks have been gaining prominence for LLM compression given their effectiveness in reducing model parameter cou

Understanding Reasoning from Pretraining to Post-Training

arXiv:2607.16097v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become central to improving large language models (LLMs) on complex reasoning tasks, yet RL post-training is l

safetyarxiv-cs-ai

Tutorials

UniDFKD: A Unified Semantic Prior Framework for Architecture-Agnostic Data-Free Knowledge Distillation

arXiv:2608.09287v1 Announce Type: cross Abstract: Data-Free Knowledge Distillation (DFKD) transfers knowledge from a pretrained teacher model to a compact student model by synthesizing semantically in

tutorialsarxiv-cs-ai

Unified Hallucination Fuzzing for Multimodal Large Language Models

arXiv:2608.07525v1 Announce Type: cross Abstract: Hallucination remains a persistent challenge for Multimodal Large Language Models (MLLMs), severely limiting their reliability in high-stakes applicat

Unimodality-Promoting Regularized Learning for Ordinal Regression

arXiv:2608.08359v1 Announce Type: new Abstract: Ordinal regression, also called ordinal classification, is classification of ordinal data, in which the underlying target variable is categorical and co

safetyarxiv-cs-lg

UniMoFlow: Grounding Instruction-Driven 3D Human Motion Editing in Generation

arXiv:2608.09143v1 Announce Type: new Abstract: Instruction-driven editing of 3D human motion requires precise spatiotemporal localization, rich semantic grounding, and strict preservation of unmodifi

local-aiarxiv-cs-cv

UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Models

arXiv:2608.08627v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) layers expand recommendation capacity through conditional computation, yet a trained checkpoint still stores and routes

Tutorials

UniScale: Arbitrary-Scale Industrial Anomaly Generation

arXiv:2608.07864v1 Announce Type: new Abstract: Industrial anomaly inspection faces a major challenge due to the lack of real-world anomaly samples. While generative models are used to create anomaly

tutorialsarxiv-cs-cv

UniSpace: Unified Visual Representation and Scalable Multimodal Modeling

arXiv:2608.08676v1 Announce Type: cross Abstract: Semantic vision encoders have become a central visual interface for multimodal understanding and semantic conditioning in image generation. However, t

researcharxiv-cs-ai

Universal or Language-Family-Specific Script Unification for Cross-Lingual Transfer? A Case Study on Turkic Languages

arXiv:2608.09356v1 Announce Type: new Abstract: Closely related languages written in different scripts expose little surface overlap to multilingual models, limiting cross-lingual transfer. We compare

applicationsarxiv-cs-cl

UNMASK: Discovering and Causally Verifying Spurious Shortcuts in Text Classifiers

model-releasesarxiv-cs-cl

arXiv:2608.09209v1 Announce Type: new Abstract: Neural language models trained on large crowdsourced corpora frequently exploit spurious surface patterns tied to target labels without true linguistic

UnsDrive: Towards Robust End-to-End Autonomous Driving in Unstructured Scenes

arXiv:2608.09098v1 Announce Type: new Abstract: End-to-end planning has shown strong promise for autonomous driving, but most existing methods are designed for structured urban roads and generalize po

safetyarxiv-cs-ro

UNSPECIFIC: General Constraint Synthesis for Breaking Copy-and-Paste Shortcut in LLM Instruction Following

model-releasesarxiv-cs-cl

arXiv:2608.09154v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly expected to follow long lists of constraints in complex instructions, and synthesizing instructions from a

Unsupervised Domain Adaptation for Multitask Image Analysis in Realistic Context with Extreme Label Shift; Application to the CTAO first Large Sized Telescope

arXiv:2608.09630v1 Announce Type: cross Abstract: Unsupervised domain adaptation is a widespread set of methods that leverages the knowledge of a labeled source domain to train a model to perform well

Unsupervised Point Cloud Registration with Self-Distillation

arXiv:2409.07558v2 Announce Type: replace Abstract: Rigid point cloud registration is a fundamental problem and highly relevant in robotics and autonomous driving. Nowadays deep learning methods can b

Unsure but Certain: Uncovering the Representation-Confidence Gap in Diffusion Language Models

arXiv:2608.08791v1 Announce Type: new Abstract: Diffusion language models use broad context to create text, suggesting they might handle input noise better than standard models. Testing reveals this i

researcharxiv-cs-cl

Unveiling the Secret of AdaLN-Zero in Diffusion Transformer

arXiv:2608.09438v1 Announce Type: new Abstract: Diffusion transformer (DiT), a rapidly emerging architecture for image generation, has gained much attention. However, despite ongoing efforts to improv

UPolarSQ: Polar Representation Learning for Optic Disc and Peripapillary Atrophy Segmentation and Quantification in Fundus Photographs

arXiv:2608.08771v1 Announce Type: new Abstract: Myopia-induced posterior-pole remodeling is frequently accompanied by Optic Disc (OD) deformation and Peripapillary Atrophy (PPA), both of which provide

Industry

Using the different models in different industries - your experience?

Hi all, I'm seeing so many conversations from people discussing how they're 'using the models wrong' and 'don't use Sol max as high is enough for you', yet all the conversations lack the nuance of wha

industryr-chatgpt

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control

arXiv:2608.07870v1 Announce Type: new Abstract: Improving sample efficiency remains a core challenge in reinforcement learning (RL), especially in real-world settings like robotics, where data collect

applicationsarxiv-cs-lg

v0.32.8

model-releasesollama-releases

Muse Glimmer Muse Glimmer is now available on all platforms. Muse Glimmer can power coding agent applications such as Claude Code, Codex, Pi and more, as well as long-running personal assistants such

v0.32.9

model-releasesollama-releases

NVIDIA Nemotron 3.5 Lightning NVIDIA Nemotron 3.5 Lightning is an open 30B mixture-of-experts (MoE) model with 3B active parameters built for that execution layer of always-on agents. It is designed f

VADER: Adaptive Debiasing for Hallucination Mitigation in Video Large Language Models

arXiv:2608.08622v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated strong performance in open-ended video understanding, yet they remain prone to fluent responses u

safetyarxiv-cs-cv

VANE: Reliable Test-Time Training for Vision-Language-Action Models via Future Visual Representation Prediction

arXiv:2608.09448v1 Announce Type: cross Abstract: Test-time training (TTT) offers a lightweight way to adapt vision--language--action (VLA) policies from unlabeled deployment streams, but it remains d

safetyarxiv-cs-cv

Variance reduction in lattice QCD observables via normalizing flows

arXiv:2603.02984v2 Announce Type: replace-cross Abstract: Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a de

researcharxiv-cs-lg

VCU-Bridge: Hierarchical Visual Connotation Understanding via Semantic Bridging

arXiv:2511.18121v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) excel on benchmarks, their processing paradigm differs from the human ability to integrate visu

Agents

VDGR-RAG: Vectors, Directories, Graphs, and Reflection Are All You Need for Unified Reasoning over Hierarchical Enterprise Knowledge

arXiv:2608.07994v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is essential for enterprise knowledge question answering (QA), particularly in domains with complex product documen

agentsarxiv-cs-ai

VectraYX-Vision-1B: A Sub-2B Spanish/LATAM Cybersecurity Vision-Language Model with Structured Visual Reasoning and Native Tool Use

model-releasesarxiv-cs-cl

arXiv:2608.08477v1 Announce Type: new Abstract: We present VectraYX-Vision-1B, a sub-2B vision-language model (VLM) for Spanish/LATAM cybersecurity imagery, coupling a frozen SigLIP-so400m encoder to

VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecasting

arXiv:2608.09286v1 Announce Type: cross Abstract: Global medium-range weather forecasting requires modeling structured yet state-dependent interactions among heterogeneous atmospheric fields. Existing

Hardware

verdi: retrieval is not transfer for continual world model optimization

arXiv:2608.09537v1 Announce Type: new Abstract: Foundation world models have made remarkable progress in planning, simulation, and embodied intelligence. However, optimizing a pretrained world model t

hardwarearxiv-cs-ai

Verication-driven closed-loop multi-agent large language modelframework for code-compliant structural design

arXiv:2608.07978v1 Announce Type: cross Abstract: Multi-agent large language model(LLM)systems are applied to structural design,yet most use one-shot generation and cannot verify their output,leaving

Verifiably grounded machine interpretation of lunar geology

arXiv:2608.09276v1 Announce Type: new Abstract: Planetary geology relies on historical, interpretive reasoning to reconstruct past events from diverse observations. Here, we present a step toward an a

local-aiarxiv-cs-cl

VeriForge: Mitigating Latent Knowledge Gaps in Narrative Drafting via Mixed-Initiative Scaffolding

arXiv:2608.09698v1 Announce Type: cross Abstract: Great fiction earns its verisimilitude through precise details, from how a longsword is gripped to pierce armor gaps to why a bleeding corpse cannot y

researcharxiv-cs-cl

Vid2WAM: Distilling Video Diffusion Priors into World Action Models

arXiv:2608.08558v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling future visual dynamics and actions. However, their scalability and generali

safetyarxiv-cs-ro

VideoVIBE: A Video-Grounded Diagnostic Benchmark for One-Shot Interactive Website Generation

arXiv:2608.09573v1 Announce Type: new Abstract: Natural-language-driven 'vibe coding' enables the one-shot generation of visually rich and interactive web applications, yet reliable assessment of thei

View-Adaptive Renderer for View-Consistent 2D-to-3D Generation

arXiv:2608.09110v1 Announce Type: new Abstract: Reconstructing 3D shapes from a single image remains a fundamental yet challenging problem in computer vision. Traditional monocular 3D generation pipel

applicationsarxiv-cs-cv

VIGIL: Tackling Hallucination Detection in Image Recontextualization

arXiv:2602.14633v2 Announce Type: replace Abstract: We introduce VIGIL (Visual Inconsistency & Generative In-context Lucidity), a benchmark dataset and framework that provides a fine-grained categoriz

Vision-Language Grounding as Bidirectional Concept Correspondence

arXiv:2608.07886v1 Announce Type: cross Abstract: Vision-language grounding connects language to visual content, yet most existing formulations reduce grounding to a unidirectional localization proble

local-aiarxiv-cs-ai

Vision Meets WiFi: Physics-Grounded Estimation of Volumetric Mechanical Properties

arXiv:2608.07726v1 Announce Type: new Abstract: Estimating volumetric mechanical properties, including Young's modulus, Poisson's ratio, and density at each voxel, is intrinsically ambiguous from visi

VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs

arXiv:2510.16598v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) encounter significant computational and memory bottlenecks from the massive number of visual tokens generat

Visual Distortion Detection in UGC Images Using Large Multimodal Models

arXiv:2608.09122v1 Announce Type: cross Abstract: The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approa

applicationsarxiv-cs-ai

Visual Token Codec: Unleashing Spatial Redundancy for ViT Feature Coding

arXiv:2608.08832v1 Announce Type: new Abstract: Distributed deployment of large vision foundation models often partitions a ViT backbone and exchanges intermediate token features between computing nod

local-aiarxiv-cs-cv

VLZip: Unified Visual and Textual Compression for Interleaved Long-Context Modeling

arXiv:2608.08630v1 Announce Type: new Abstract: Vision Language Models (VLMs) face significant challenges with ultra-long, interleaved image-text sequences due to the quadratic complexity of self-atte