All entries

Leveraging Vision-Language Models to Detect Attention in Educational Videos

model-releasesarxiv-cs-cv

arXiv:2605.20211v1 Announce Type: new Abstract: Educational videos are a cornerstone of remote and blended learning. However, learners' fluctuating attention remains a significant barrier to effective

License to Stream: ‘007 First Light’ Coming to GeForce NOW With an Ultimate Bundle

DGX agent

The mission begins now. GeForce NOW is dialing up the action with a blockbuster mix of spy thrills, high-speed racing and member rewards — plus eight new games joining the cloud this week, all ready t

hardwarenvidia-blog

21 May 2026

Lighting-aware Unified Model for Instance Segmentation

arXiv:2605.20436v1 Announce Type: new Abstract: Foundation models like the Segment Anything Model (SAM) demonstrate impressive zero-shot generalization but frequently degrade under diverse real-world

applicationsarxiv-cs-cv

Linear-DPO: Linear Direct Preference Optimization for Diffusion and Flow-Matching Generative Models

arXiv:2605.21123v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) is successful for alignment in LLMs but still faces challenges in text-to-image generation. Existing studies are co

safetyarxiv-cs-cv

Lip sync and Lora

local-air-stablediffusion

LoRA models can be used with image-to-video workflows to create automatic lip-syncing effects by controlling camera movements and instructing the model to synchronize audio with mouth movements. This

Lisbon Machine Learning School (LxMLS 2026) [D]

researchr-machinelearning

LxMLS 2026 is a 6-day in-person event scheduled for July 20-25 at Instituto Superior Técnico that covers machine learning topics from theory to practice for solving natural language processing problem

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex

arXiv:2605.06139v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard approach for large language models (LLMs) post-training to incentivize r

safetyarxiv-cs-lg

LiteViLNet: Lightweight Vision-LiDAR Fusion Network for Efficient Road Segmentation

arXiv:2605.21007v1 Announce Type: new Abstract: Road segmentation is a fundamental perception task for autonomous driving and intelligent robotic systems, requiring both high accuracy and real-time in

agentsarxiv-cs-cv

Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU

model-releasesarxiv-cs-lg

arXiv:2605.20706v1 Announce Type: cross Abstract: Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contendin

LLM Pretraining Shapes a Generalizable Manifold: Insights into Cross-Modal Transfer to Time Series

arXiv:2605.20449v1 Announce Type: new Abstract: Can language-pretrained transformers become effective time-series forecasters, and why? In this paper, we show that cross-modal transfer arises because

safetyarxiv-cs-lg

Tutorials

LLM training is built on fast MatMuls. But many surrounding ops still run as memory-bound kernels. CODA reparameterizes them to hide in the …

tutorialsjeremy-howard--x

LLM training is built on fast MatMuls. But many surrounding ops still run as memory-bound kernels. CODA reparameterizes them to hide in the matmul’s shadow, fused into its epilogue before results leav

LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws

model-releasesarxiv-cs-cl

arXiv:2502.12120v3 Announce Type: replace-cross Abstract: Scaling laws guide the development of large language models (LLMs) by offering estimates for the optimal balance of model size, tokens, and co

Local-sensitive connectivity filter (ls-cf): A post-processing unsupervised improvement of the frangi, hessian and vesselness filters for multimodal vessel segmentation

arXiv:2605.21251v1 Announce Type: cross Abstract: A retinal vessel analysis is a procedure that can be used as an assessment of risks to the eye. This work proposes an unsupervised multimodal approach

researcharxiv-cs-cv

LoCar: Localization-Aware Evaluation of In-Vehicle Assistants through Fine-Grained Sociolinguistic Control

arXiv:2605.21086v1 Announce Type: new Abstract: While Large Language Models (LLMs) are increasingly integrated into in-vehicle conversational systems, identifying the optimal model remains challenging

local-aiarxiv-cs-cl

Industry

London Mayor Sadiq Khan blocks the Met police's £50M Palantir deal to automate intelligence analysis, citing a 'clear and serious breach' of procurement rules (Robert Booth/The Guardian)

Robert Booth / The Guardian: London Mayor Sadiq Khan blocks the Met police's £50M Palantir deal to automate intelligence analysis, citing a “clear and serious breach” of procurement rules — Exclusive:

industrytechmeme

Long-Context Reasoning Through Proxy-Based Chain-of-Thought Tuning

arXiv:2605.20201v1 Announce Type: new Abstract: Recent large language models support inputs of up to 10 million tokens, yet they perform poorly on long-context tasks that require complex reasoning. Su

researcharxiv-cs-cl

longer comment on yesterday’s stories

longer comment on yesterday’s stories the nuance between yesterday’s stories that X influencers won’t tell you: https://open.substack.com/pub/garymarcus/p/checking-the-math-behind-openai-and?r=8tdk6&u

safetygary-marcus--x

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging

arXiv:2605.20866v1 Announce Type: new Abstract: Communication is a major bottleneck in distributed learning, especially in large-scale settings and in federated learning environments with slow links.

local-aiarxiv-cs-lg

Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs

arXiv:2605.21446v1 Announce Type: new Abstract: Interpretable autonomous driving planners depend not only on generating explanations, but also on those explanations remaining reliable under real-world

safetyarxiv-cs-ro

Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition

arXiv:2605.20735v1 Announce Type: new Abstract: This paper proposes two new open-source iris recognition algorithms, providing both Python and IREX-compliant C++ implementations to be submitted to the

researcharxiv-cs-cv

Tutorials

LT2: Linear-Time Looped Transformers

arXiv:2605.20670v1 Announce Type: new Abstract: Looped Transformers (LT) have emerged as a powerful architecture by iterating their layers multiple times before decoding the final token. However, pair

tutorialsarxiv-cs-lg

LTX 2.3 + LTX Director is a Huge improvement

local-air-stablediffusion

LTX-2.3 is a multimodal video generation model developed by Lightricks that generates synchronized audio and video in a single forward pass at resolutions up to 4K at 50 frames per second. The model i

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy

arXiv:2507.06929v2 Announce Type: replace-cross Abstract: We investigate Machine-Learned Force Fields (MLFFs) trained on approximate Density Functional Theory (DFT) and Coupled Cluster (CC) level pote

Machine-Learning-Enhanced Non-Invasive Testing for MASLD Fibrosis: Shallow-Deep Neural Networks Versus FIB-4, Tabular Foundation Models, and Large Language Models

arXiv:2605.20523v1 Announce Type: new Abstract: Advanced fibrosis is a major determinant of liver-related morbidity in metabolic dysfunction-associated steatotic liver disease (MASLD). FIB-4 is widely

MagBridge-Battery: A Synthetic Bridge Dataset for Li-ion Magnetometry and State-of-Health Diagnostics

model-releasesarxiv-cs-lg

arXiv:2605.20240v1 Announce Type: new Abstract: Battery health diagnostics today rely overwhelmingly on electrochemical signals measured at the cell terminals. A parallel literature has shown that mag

MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models

MagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and orchestration to support efficient agent

agentsmicrosoft-research

Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX

arXiv:2605.20577v1 Announce Type: cross Abstract: Riichi Mahjong is a multi-player, imperfect-information game characterized by stochasticity and high-dimensional state spaces. These attributes presen

safetyarxiv-cs-lg

Major advances in AI and 3D medical imaging are changing what patients see in the exam room

Even as AI rewrites the rules across industries, healthcare is still confronting a half-century of diagnostic stasis — but a new generation of companies is betting that advances in AI and 3D medical i

applicationssiliconangle

Managed Deep Agents is now in Private Beta ICYMI: It’s managed, model-agnostic infra for deep agents you can deploy with a single line of co…

applicationsharrison-chase--x

Managed Deep Agents is a new LangChain feature in private beta that provides managed infrastructure for deep agents, designed to be model-agnostic and deployable with minimal code. The service aims to

Manga109-v2026: Revisiting Manga109 Annotations for Modern Manga Understanding

arXiv:2605.21182v1 Announce Type: new Abstract: Manga is a culturally distinctive multimodal medium and one of the most influential forms of Japanese popular culture. As AI systems increasingly target

researcharxiv-cs-cl

Map-Mono-Ego: Map-Grounded Global Human Pose Estimation from Monocular Egocentric Video

arXiv:2605.20889v1 Announce Type: new Abstract: Monocular egocentric human pose estimation is essential for ubiquitous activity monitoring. However, understanding the user's absolute location within t

researcharxiv-cs-cv

MAPS: A Synthetic Dataset for Probing Vision Models in a Controlled 3D Scene Space

arXiv:2605.20549v1 Announce Type: new Abstract: Modern vision models achieve strong performance on standard benchmarks, yet their aggregate accuracy reveals little about which scene properties drive t

applicationsarxiv-cs-cv

Industry

Marc Andreessen (@pmarca) on what it’s like to work at SpaceX: “It’s like being dropped into a zone of shocking competence.” “Everybody is u…

Marc Andreessen (@pmarca) on what it’s like to work at SpaceX: “It’s like being dropped into a zone of shocking competence.” “Everybody is ultra competent, and the reason everybody’s ultra competent i

industryelon-musk--x

Markovian Circuit Tracing for Transformer State Dynamic

model-releasesarxiv-cs-lg

arXiv:2605.20824v1 Announce Type: new Abstract: Many sequence computations are easier to study as movement through internal states than as isolated local circuits. We introduce Markovian Circuit Traci

MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing

arXiv:2603.06007v2 Announce Type: replace Abstract: Large language model-based (LLM-based) multi-agent systems (MAS) are increasingly used to extend agentic problem solving via role specialization and

agentsarxiv-cs-cl

Math is easy* because it has verifiable outputs and few messy judgement choices to make. Which AI labs have the guts to make advancing socia…

applicationsethan-mollick--x

Math is easy* because it has verifiable outputs and few messy judgement choices to make. Which AI labs have the guts to make advancing social science a priority? It may actually do more for human flou

Matryoshka Concept Bottleneck Models

arXiv:2605.20612v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) have emerged as a prominent paradigm for interpretable deep learning, learning by grounding predictions in human-unders

Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference

arXiv:2511.21223v2 Announce Type: replace-cross Abstract: Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models. However, its formul

Industry

May this era be the new dawn of humanity.

Elon Musk posted an aspirational message expressing hope that the current period represents a transformative new beginning for humanity. The post reflects optimistic sentiment about future progress an

industryelon-musk--x

MC-Risk: Multi-Component Risk Fields for Risk Identification and Motion Planning

arXiv:2605.21406v1 Announce Type: new Abstract: We present MC-Risk, a planner-aligned, multi-component risk field on a bird's-eye-view grid that yields early, calibrated, and class-aware risk localiza

agentsarxiv-cs-ro

Measuring and mitigating overreliance to build human-compatible AI

arXiv:2509.08010v2 Announce Type: replace-cross Abstract: Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable o

applicationsarxiv-cs-cl

Mechanics of Bias and Reasoning: Interpreting the Impact of Chain-of-Thought Prompting on Gender Bias in LLMs

model-releasesarxiv-cs-cl

arXiv:2605.20410v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in socially sensitive settings despite substantial documentation that they encode gender biases.

Mechanisms of Misgeneralization in Physical Sequence Modeling

arXiv:2605.20299v1 Announce Type: new Abstract: Generative sequence models are often trained to plan motion in physical domains, from robotics to mechanical simulations. When constructing a dataset to

local-aiarxiv-cs-lg

Mechanistic Interpretability for Learning Assurance of a Vision-Based Landing System

arXiv:2605.20607v1 Announce Type: cross Abstract: EASA's learning-assurance guidance requires data-driven aviation systems to build and monitor their own situation representation, yet for neural netwo

safetyarxiv-cs-cv

MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery

model-releasesarxiv-cs-cv

arXiv:2605.20297v1 Announce Type: new Abstract: Medical image segmentation faces a fundamental challenge in continual learning: data arrives sequentially from heterogeneous sources, yet effective cont

MedicalBench: Evaluating Large Language Models Toward Improved Medical Concept Extraction

model-releasesarxiv-cs-cl

arXiv:2605.20197v1 Announce Type: new Abstract: Medical concept extraction from electronic health records underpins many downstream applications, yet remains challenging because medically meaningful c

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Cod…

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Coding agent, end to end. Frontend prototypes, multi-file refactor

model-releasesqwen--x

Mem-pi: Adaptive Memory through Learning When and What to Generate

arXiv:2605.21463v1 Announce Type: new Abstract: We present Mem-pi, a framework for adaptive memory in large language model (LLM) agents, where useful guidance is generated on demand rather than retrie

agentsarxiv-cs-cl