All entries

Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any f…

model-releasesharrison-chase--x

Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any frontier model selection. Till now we have mostly focused on

Industry

Two-year-old Surface PCs get 300 price hikes as sub-1,000 models go away

DGX agent

Microsoft silently raised prices on practically all of its Surface PCs by between 100 and 500 , with the last two models previously under 1,000 — the Surface Pro 12-inch and Surface Laptop 13-inch, wh

industryars-technica

14 Apr 2026

U^{2}Flow: Uncertainty-Aware Unsupervised Optical Flow Estimation

arXiv:2604.10056v1 Announce Type: new Abstract: Unsupervised optical flow methods typically lack reliable uncertainty estimation, limiting their robustness and interpretability. We propose U^{2}Flow,

tutorialsarxiv-cs-cv

Uber CTO Praveen Neppalli Naga says the company's surging use of AI coding tools has maxed out its full-year AI budget just a few months into 2026 (Laura Bratton/The Information)

Laura Bratton / The Information: Uber CTO Praveen Neppalli Naga says the company's surging use of AI coding tools has maxed out its full-year AI budget just a few months into 2026 — Uber's surging use

model-releasestechmeme

Local Ai

UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems

arXiv:2602.17709v2 Announce Type: replace-cross Abstract: All-atom molecular simulation serves as a quintessential ``computational microscope'' for understanding the machinery of life, yet it remains

local-aiarxiv-cs-ai

UDAPose: Unsupervised Domain Adaptation for Low-Light Human Pose Estimation

arXiv:2604.10485v1 Announce Type: cross Abstract: Low-visibility scenarios, such as low-light conditions, pose significant challenges to human pose estimation due to the scarcity of annotated low-ligh

Local Ai

UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling

arXiv:2604.11014v1 Announce Type: new Abstract: Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chrom

local-aiarxiv-cs-cv

UK gov's Mythos AI tests help separate cybersecurity threat from hype

model-releasesars-technica

The UK's AI Security Institute (AISI) conducted evaluations of Anthropic's Claude Mythos Preview, finding it represents a meaningful step up over previous frontier AI models in cybersecurity capabilit

Ukraine’s military robot surge aims to offset drone risks to humans

Ukraine's surge in ground robots (unmanned ground vehicles, or UGVs) is driven by the rise of aerial drones, which have turned vast swaths of the battlefield into lethal kill zones. These robots are u

industryars-technica

Ultra-Low-Dimensional Prompt Tuning via Random Projection

model-releasesarxiv-cs-cl

arXiv:2502.04501v3 Announce Type: replace Abstract: Large language models achieve state-of-the-art performance but are increasingly costly to fine-tune. Prompt tuning is a parameter-efficient fine-tun

Uncertainty-Aware Web-Conditioned Scientific Fact-Checking

arXiv:2604.11036v1 Announce Type: cross Abstract: Scientific fact-checking is vital for assessing claims in specialized domains such as biomedicine and materials science, yet existing systems often ha

Uncertainty-Based Ensemble Learning in CMR Semantic Segmentation

arXiv:2502.09269v3 Announce Type: replace Abstract: Existing methods derive clinical functional metrics from ventricular semantic segmentation in cardiac cine sequences. While performing well on overa

Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation

arXiv:2604.10823v1 Announce Type: new Abstract: Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate bac

Uncertainty-quantified Pulse Signal Recovery from Facial Video using Regularized Stochastic Interpolants

model-releasesarxiv-cs-cv

arXiv:2604.10777v1 Announce Type: new Abstract: Imaging Photoplethysmography (iPPG), an optical procedure which recovers a human's blood volume pulse (BVP) waveform using pixel readout from a camera,

Applications

Understanding Generalization in Role-Playing Models via Information Theory

arXiv:2512.17270v2 Announce Type: replace-cross Abstract: Role-playing models (RPMs) are widely used in real-world applications but underperform when deployed in the wild. This degradation can be attr

applicationsarxiv-cs-ai

Unfolding 3D Gaussian Splatting via Iterative Gaussian Synopsis

arXiv:2604.11685v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting

model-releasesarxiv-cs-lg

arXiv:2604.11257v1 Announce Type: new Abstract: Graph Data Prompt (GDP), which introduces specific prompts in graph data for efficiently adapting pre-trained GNNs, has become a mainstream approach to

Unified Removal of Raindrops and Reflections: A New Benchmark and A Novel Pipeline

model-releasesarxiv-cs-cv

arXiv:2603.16446v3 Announce Type: replace Abstract: When capturing images through glass surfaces or windshields on rainy days, raindrops and reflections frequently co-occur to significantly reduce the

Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning

arXiv:2602.21484v2 Announce Type: replace Abstract: 3D object detection is essential for autonomous driving and robotic perception, yet its reliance on large-scale manually annotated data limits scala

agentsarxiv-cs-cv

Unifying Ontology Construction and Semantic Alignment for Deterministic Enterprise Reasoning at Scale

arXiv:2604.09608v1 Announce Type: new Abstract: While enterprises amass vast quantities of data, much of it remains chaotic and effectively dormant, preventing decision-making based on comprehensive i

UNIGEOCLIP: Unified Geospatial Contrastive Learning

arXiv:2604.11668v1 Announce Type: new Abstract: The growing availability of co-located geospatial data spanning aerial imagery, street-level views, elevation models, text, and geographic coordinates o

safetyarxiv-cs-cv

Unilateral Relationship Revision Power in Human-AI Companion Interaction

arXiv:2603.23315v3 Announce Type: replace-cross Abstract: When providers update AI companions, users report grief, betrayal, and loss. A growing literature asks whether the norms governing personal re

agentsarxiv-cs-ai

UniPROT: Uniform Prototype Selection via Partial Optimal Transport with Submodular Guarantees

arXiv:2604.10952v1 Announce Type: new Abstract: Selecting prototypical examples from a source distribution to represent a target data distribution is a fundamental problem in machine learning. Existin

researcharxiv-cs-lg

UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents

arXiv:2604.11557v1 Announce Type: new Abstract: Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However

Universal statistical signatures of evolution in artificial intelligence architectures

arXiv:2604.10571v1 Announce Type: cross Abstract: We test whether artificial intelligence architectural evolution obeys the same statistical laws as biological evolution. Compiling 935 ablation experi

Universality of first-order methods on random and deterministic matrices

arXiv:2604.11729v1 Announce Type: cross Abstract: General first-order methods (GFOM) are a flexible class of iterative algorithms which update a state vector by matrix-vector multiplications and entry

tutorialsarxiv-cs-lg

Unmixing-Guided Spatial-Spectral Mamba with Clustering Tokens for Hyperspectral Image Classification

arXiv:2604.09948v1 Announce Type: new Abstract: Although hyperspectral image (HSI) classification is critical for supporting various environmental applications, it is a challenging task due to the spe

tutorialsarxiv-cs-cv

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN

arXiv:2509.25612v2 Announce Type: replace-cross Abstract: Ensuring power grid resilience requires the timely and unsupervised detection of anomalies in synchrophasor data streams. We introduce T-BiGAN

Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation

model-releasesarxiv-cs-lg

arXiv:2509.20587v3 Announce Type: replace-cross Abstract: We study an unsupervised domain adaptation problem where the source domain consists of subpopulations defined by the binary label Y and a bina

US affidavit: the man charged with attacking Sam Altman's home had a document that 'identified views opposed' to AI and listed addresses of other AI executives (New York Times)

New York Times: US affidavit: the man charged with attacking Sam Altman's home had a document that “identified views opposed” to AI and listed addresses of other AI executives — The authorities said a

industrytechmeme

US-based Credo, which specializes in data center connectivity, agrees to acquire Israeli chip startup DustPhotonics in a cash-and-stock deal worth up to $1.3B (CTech)

CTech: US-based Credo, which specializes in data center connectivity, agrees to acquire Israeli chip startup DustPhotonics in a cash-and-stock deal worth up to $1.3B — The Israeli company's photonic c

industrytechmeme

Use-case based deployments on SageMaker JumpStart

We're excited to announce the launch of Amazon SageMaker JumpStart optimized deployments. SageMaker JumpStart improved deployments address the need for rich and straightforward deployment customizatio

industryaws-ml-blog

Use of AI Tools: Guidelines to Maintain Academic Integrity in Computing Colleges

arXiv:2604.11111v1 Announce Type: cross Abstract: The rapid adoption of AI tools such as ChatGPT has significantly transformed academic practices, offering considerable benefits for both students and

tutorialsarxiv-cs-ai

Users accuse Anthropic of degrading Claude Opus 4.6's and Claude Code's performance; the startup's employees publicly deny it degrades models to manage capacity (Carl Franzen/VentureBeat)

Carl Franzen / VentureBeat: Users accuse Anthropic of degrading Claude Opus 4.6's and Claude Code's performance; the startup's employees publicly deny it degrades models to manage capacity — A growing

model-releasestechmeme

Using Deep Learning Models Pretrained by Self-Supervised Learning for Protein Localization

arXiv:2604.10970v1 Announce Type: new Abstract: Background: Task-specific microscopy datasets are often small, making it difficult to train deep learning models that learn robust features. While self-

tutorialsarxiv-cs-cv

Using Unwrapped Full Color Space Palette Recording to Measure Exposedness of a Vehicle Exterior Parts for External Human Machine Interfaces

arXiv:2604.11406v1 Announce Type: new Abstract: One of the concerns with autonomous vehicles is their ability to communicate their intent to other road users, specially pedestrians, in order to preven

agentsarxiv-cs-ro

Utilizing and Calibrating Hindsight Process Rewards via Reinforcement with Mutual Information Self-Evaluation

arXiv:2604.11611v1 Announce Type: new Abstract: To overcome the sparse reward challenge in reinforcement learning (RL) for agents based on large language models (LLMs), we propose Mutual Information S

safetyarxiv-cs-cl

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

arXiv:2604.03147v2 Announce Type: replace-cross Abstract: We present a method to identify a valence-arousal (VA) subspace within large language model representations. From 211k emotion-labeled texts,

Variable Selection Using Relative Importance Rankings

model-releasesarxiv-cs-lg

arXiv:2509.10853v2 Announce Type: replace-cross Abstract: Although conceptually related, variable selection and relative importance (RI) analysis have been treated quite differently in the literature.

Variance-Aware Prior-Based Tree Policies for Monte Carlo Tree Search

arXiv:2512.21648v2 Announce Type: replace-cross Abstract: Monte Carlo Tree Search (MCTS) has profoundly influenced reinforcement learning (RL) by integrating planning and learning in tasks requiring l

safetyarxiv-cs-ai

Variational Latent Entropy Estimation Disentanglement: Controlled Attribute Leakage for Face Recognition

arXiv:2604.11250v1 Announce Type: new Abstract: Face recognition embeddings encode identity, but they also encode other factors such as gender and ethnicity. Depending on how these factors are used by

safetyarxiv-cs-cv

Variational Visual Question Answering for Uncertainty-Aware Selective Prediction

arXiv:2505.09591v3 Announce Type: replace-cross Abstract: Despite remarkable progress in recent years, Vision Language Models (VLMs) remain prone to overconfidence and hallucinations on tasks such as

Vector Field Synthesis with Sparse Streamlines Using Diffusion Model

arXiv:2604.09838v1 Announce Type: new Abstract: We present a novel diffusion-based framework for synthesizing 2D vector fields from sparse, coherent inputs (i.e., streamlines) while maintaining physic

Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis

arXiv:2604.10800v1 Announce Type: cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified concl

agentsarxiv-cs-ai

VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation

model-releasesarxiv-cs-cl

arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod

VeriSim: A Configurable Framework for Evaluating Medical AI Under Realistic Patient Noise

arXiv:2604.10441v1 Announce Type: new Abstract: Medical large language models (LLMs) achieve impressive performance on standardized benchmarks, yet these evaluations fail to capture the complexity of

VeriTrans: Fine-Tuned LLM-Assisted NL-to-PL Translation via a Deterministic Neuro-Symbolic Pipeline

arXiv:2604.10341v1 Announce Type: new Abstract: extbf{VeriTrans} is a reliability-first ML system that compiles natural-language requirements into solver-ready logic with validator-gated reliability.

safetyarxiv-cs-ai

Applications

Version numbers are not a very useful way to understand model ability gains at this stage. Unfortunately that means that if you aren’t follo…

applicationsethan-mollick--x

Version numbers are not a very useful way to understand model ability gains at this stage. Unfortunately that means that if you aren’t following closely, you would expect that 5.4 is a small gain over