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Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning

arXiv:2605.14717v1 Announce Type: cross Abstract: Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cytometry, yet inferring molecular phenotypes directl

researcharxiv-cs-ai

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Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy

DGX agent

arXiv:2605.14253v1 Announce Type: new Abstract: Purpose: Mechanical thrombectomy (MT) improves stroke outcomes, but is limited by a lack of local treatment access. Widespread distribution of reinforce

local-aiarxiv-cs-cv

15 May 2026

Hardware

Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines

arXiv:2605.13981v1 Announce Type: cross Abstract: The rise in deployment of large language models has driven a surge in GPU demand and datacenter scaling, raising concerns about electricity use, grid

hardwarearxiv-cs-ai

Towards Robotic Dexterous Hand Intelligence: A Survey

arXiv:2605.13925v1 Announce Type: new Abstract: Robotic dexterous hands are central to contact-rich manipulation, with rapid progress driven by advances in hardware, sensing, control, simulation, and

researcharxiv-cs-ro

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning

arXiv:2605.13936v1 Announce Type: cross Abstract: The recent success of large language models (LLMs) has been largely driven by vast public datasets. However, the next frontier for LLM development lie

Training-Free Generative Sampling via Moment-Matched Score Smoothing

arXiv:2605.14276v1 Announce Type: cross Abstract: Diffusion models generate samples by denoising along the score of a perturbed target distribution. In practice, one trains a neural diffusion model, w

Training-Free Inference for High-Resolution Sinogram Completion

arXiv:2506.08809v5 Announce Type: replace Abstract: High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While

local-aiarxiv-cs-cv

Training ML Models with Predictable Failures

arXiv:2605.15134v1 Announce Type: new Abstract: Estimating how often an ML model will fail at deployment scale is central to pre-deployment safety assessment, but a feasible evaluation set is rarely l

TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning

arXiv:2510.07118v3 Announce Type: replace Abstract: Instruction tuning is essential for aligning large language models (LLMs) to downstream tasks and commonly relies on large, diverse corpora. However

researcharxiv-cs-cl

TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models

arXiv:2602.04657v3 Announce Type: replace Abstract: Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most ex

local-aiarxiv-cs-cv

Tutorials

TurboVGGT: Fast Visual Geometry Reconstruction with Adaptive Alternating Attention

arXiv:2605.14315v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction methods, such as visual geometry transformers, have substantially advanced the traditional per-scene optimization

tutorialsarxiv-cs-cv

Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization

arXiv:2605.14373v1 Announce Type: cross Abstract: Zeroth-Order (ZO) optimization is pivotal for scenarios where backpropagation is unavailable, such as memory-constrained on-device learning and black-

local-aiarxiv-cs-ai

Agents

turns out that building evals is super super challenging even now. i thought a lot of it was table stakes but turns out it has only become h…

turns out that building evals is super super challenging even now. i thought a lot of it was table stakes but turns out it has only become harder since agents are now more complex than ever! going to

agentsharrison-chase--x

UMo: Unified Sparse Motion Modeling for Real-Time Co-Speech Avatars

arXiv:2605.14731v1 Announce Type: cross Abstract: Speech-driven gestures and facial animations are fundamental to expressive digital avatars in games, virtual production, and interactive media. Howeve

Unbiased and Second-Order-Free Training for High-Dimensional PDEs

arXiv:2605.14643v1 Announce Type: new Abstract: Deep learning methods based on backward stochastic differential equations (BSDEs) have emerged as competitive alternatives to physics-informed neural ne

Uncertainty Quantification for Large Language Diffusion Models

arXiv:2605.14570v1 Announce Type: new Abstract: Large Language Diffusion Models (LLDMs) are emerging as an alternative to autoregressive models, offering faster inference through higher parallelism. S

researcharxiv-cs-cl

Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces

arXiv:2605.14358v1 Announce Type: new Abstract: Language models often generate long chain-of-thought traces, but it remains unclear how much of this reasoning is necessary for preserving the final pre

local-aiarxiv-cs-ai

Uncovering Trajectory and Topological Signatures in Multimodal Pediatric Sleep Embeddings

arXiv:2605.14156v1 Announce Type: new Abstract: While generative models have shown promise in pediatric sleep analysis, the latent structure of their multimodal embeddings remains poorly understood. T

researcharxiv-cs-lg

Understanding How International Students in the U.S. Are Using Conversational AI to Support Cross-Cultural Adaptation

arXiv:2605.15127v1 Announce Type: cross Abstract: Moving to a new culture and adapting to a new life, as an international student, can be a stressful experience. In the US, international students face

Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning

arXiv:2605.14785v1 Announce Type: cross Abstract: Neural networks suffer from catastrophic forgetting in class-incremental learning (CIL) settings. Rehearsalnicode{x2013}replaying a subset of past sam

researcharxiv-cs-cv

Unified Pix Token And Word Token Generative Language Model

model-releasesarxiv-cs-cv

arXiv:2605.14028v1 Announce Type: new Abstract: Since the emergence of Vision Transformer (ViT), it has been widely used in generative language model and generative visual model. Especially in the cur

UniTriGen: Unified Triplet Generation of Aligned Visible-Infrared-Label for Few-Shot RGB-T Semantic Segmentation

arXiv:2605.14626v1 Announce Type: new Abstract: RGB-T semantic segmentation requires strictly aligned VIS-IR-Label triplets; however, such aligned triplet data are often scarce in real-world scenarios

Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning

arXiv:2605.14876v1 Announce Type: cross Abstract: Despite rapid advancements, current text-to-image (T2I) models predominantly rely on a single-step generation paradigm, which struggles with complex s

Unsteady Metrics and Benchmarking Cultures of AI Model Builders

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases

Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling

arXiv:2605.13933v1 Announce Type: cross Abstract: Acquisition differences across sites, scanners, and protocols in dMRI introduce variability that complicates structural connectome analysis. This moti

Unsupervised simulation of incompressible flows with physics- and equality- constrained artificial neural networks

arXiv:2511.18820v2 Announce Type: replace-cross Abstract: Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations, yet their success in simulating incomp

researcharxiv-cs-lg

Tools

Use native curl syntax with Vercel CLI

The Vercel CLI now supports native curl syntax, allowing developers to use standard curl commands directly within the CLI tool instead of requiring alternative command formats. This enhancement improv

toolsvercel-blog

v0.25.0-rc0: ci: speed up release builds (#15982)

This release candidate introduces CI/CD optimizations to accelerate the release build process for Ollama, as indicated by pull request #15982. The improvements focus on reducing build times during the

local-aiollama-releases

V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

arXiv:2603.11042v2 Announce Type: replace-cross Abstract: Generating music that temporally aligns with video events is challenging for existing text-to-music models, which lack fine-grained temporal c

safetyarxiv-cs-ai

VectraYX-Nano: A 42M-Parameter Spanish Cybersecurity Language Model with Curriculum Learning and Native Tool Use

model-releasesarxiv-cs-cl

arXiv:2605.13989v1 Announce Type: new Abstract: We present VectraYX-Nano, a 41.95M-parameter decoder-only language model trained from scratch in Spanish for cybersecurity, with a Latin-American focus

Agents

Veeam CEO Anand Eswaran says the company’s future is providing the AI stack’s missing layer

Agentic AI might be outrunning the one thing it needs most — an AI trust layer. That challenge is reshaping the ambitions of companies long anchored in data protection. Veeam Software Group GmbH, whic

agentssiliconangle

Vendor-Conditioned Contrastive Learning for Predicting Organizational Cyber Threat Targets

model-releasesarxiv-cs-lg

arXiv:2012.14425v2 Announce Type: replace-cross Abstract: Cyberattacks cause billions of dollars in damage annually, with malicious hackers often sharing exploit code and techniques on underground for

Venus-DeFakerOne: Unified Fake Image Detection & Localization

arXiv:2605.14091v1 Announce Type: new Abstract: In recent years, the rapid evolution of generative AI has fundamentally reshaped the paradigm of image forgery, breaking the traditional boundaries betw

local-aiarxiv-cs-cv

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

arXiv:2510.05213v2 Announce Type: replace-cross Abstract: Pretrained vision foundation models (VFMs) advance robotic learning via rich visual representations, yet individual VFMs typically excel only

VerbalValue: A Socially Intelligent Virtual Host for Sales-Driven Live Commerce

arXiv:2605.14542v1 Announce Type: new Abstract: A skilled live-commerce host is not merely a narrator, but a sales agent who converts viewer curiosity into purchase intent through expert product knowl

Very thoughtful post on the role and success of open source, including potential applications for AVs and AI. Long, but worth the read. -- '…

Very thoughtful post on the role and success of open source, including potential applications for AVs and AI. Long, but worth the read. -- 'Open source is no longer just how good software gets built.

safetyclem-delangue--x

VGGT-360: Geometry-Consistent Zero-Shot Panoramic Depth Estimation

arXiv:2603.18943v2 Announce Type: replace Abstract: This paper presents VGGT-360, a novel training-free framework for zero-shot, geometry-consistent panoramic depth estimation. Unlike prior view-indep

researcharxiv-cs-cv

VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction

arXiv:2605.15186v1 Announce Type: cross Abstract: High-quality 3D scene reconstruction has recently advanced toward generalizable feed-forward architectures, enabling the generation of complex environ

researcharxiv-cs-ai

VGGT-Omega

arXiv:2605.15195v1 Announce Type: new Abstract: Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing

Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation

arXiv:2602.02994v2 Announce Type: replace Abstract: Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet

Video-Zero: Self-Evolution Video Understanding

arXiv:2605.14733v1 Announce Type: new Abstract: Self-evolution offers a promising path for improving reasoning models without relying on intensive human annotation. However, extending this paradigm to

researcharxiv-cs-cv

Agents

Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining

arXiv:2605.14747v1 Announce Type: cross Abstract: Recent advances in multimodal large language models have driven growing interest in graphical user interface (GUI) agents, yet their generalization re

agentsarxiv-cs-ai

ViMU: Benchmarking Video Metaphorical Understanding

model-releasesarxiv-cs-cv

arXiv:2605.14607v1 Announce Type: new Abstract: Any new medium, once it emerges, is used for more than the transmission of overt content alone. The information it carries typically operates on two lev

Vision-Based Runtime Monitoring under Varying Specifications using Semantic Latent Representations

model-releasesarxiv-cs-cv

arXiv:2605.13923v1 Announce Type: cross Abstract: We study certified runtime monitoring of past-time signal temporal logic (ptSTL) from visual observations under partial observability. The monitor mus

Vision-Based Water Level and Flow Estimation

arXiv:2605.14645v1 Announce Type: cross Abstract: With the rapid evolution of computer vision, vision-based methodologies for water level and river surface velocity estimation have reached significant

researcharxiv-cs-ai

Vision-Core Guided Contrastive Learning for Balanced Multi-modal Prognosis Prediction of Stroke

arXiv:2605.14710v1 Announce Type: cross Abstract: Deep learning and multi-modal fusion have demonstrated transformative potential in medical diagnosis by integrating diverse data sources. However, acc

safetyarxiv-cs-ai

Vision-LLMs for Spatiotemporal Traffic Forecasting

arXiv:2510.11282v2 Announce Type: replace Abstract: Accurate spatiotemporal traffic forecasting is a critical prerequisite for proactive resource management in dense urban mobile networks. While large

Viverra: Text-to-Code with Guarantees

arXiv:2605.14972v1 Announce Type: cross Abstract: A fundamental limitation of Text-to-Code is that no guarantee can be obtained about the correctness of the generated code. Therefore, to ensure its co

safetyarxiv-cs-ai