All entries

Israeli startup Frame Security, which protects organizations from AI-powered social engineering attacks, emerges from stealth with $50M led by Index and others (CTech)

CTech: Israeli startup Frame Security, which protects organizations from AI-powered social engineering attacks, emerges from stealth with $50M led by Index and others — The Israeli firm aims to modern

industrytechmeme

Content type

All Blog X Post Paper YouTube Reddit GitHub

Safety

It is insane that we allow big tech to race toward superintelligence without any oversight. This is a grave national security risk. Industry…

DGX agent

It is insane that we allow big tech to race toward superintelligence without any oversight. This is a grave national security risk. Industry will not regulate itself. Get trained with Torchbearer to a

safetyconnor-leahy--x

11 May 2026

Applications

It is one reason why I think the push for smaller, local models is more complicated than people think. If you want good answers, especially …

applicationsethan-mollick--x

It is one reason why I think the push for smaller, local models is more complicated than people think. If you want good answers, especially good answers to unexpected problems, frontier models will ge

It Just Takes Two: Scaling Amortized Inference to Large Sets

arXiv:2605.07972v1 Announce Type: cross Abstract: Neural posterior estimation has emerged as a powerful tool for amortized inference, with growing adoption across scientific and applied domains. In ma

'It would be a mistake for any country to try to slow down open source. A country that leads open source is a country that can lead AI in ge…

'It would be a mistake for any country to try to slow down open source. A country that leads open source is a country that can lead AI in general' @ClementDelangue, co-founder & CEO @HuggingFace Watch

industryclem-delangue--x

Tools

I've been using HTML for planning, speccing, exploration, code review, reports and a lot more. https://x.com/trq212/status/20528098857637479…

HTML is being used beyond traditional web development as a versatile tool for planning, specifications, exploratory work, code review documentation, and report generation. This approach leverages HTML

toolsthariq--x

Joanna Stern is not a robot, but she lived with them

My guest today is longtime friend of the show Joanna Stern. You all know Joanna: she is the former senior personal technology columnist for The Wall Street Journal, a former Decoder guest host, one of

industrythe-verge-ai

Kernel Selection is Model Selection: A Unified Complexity-Penalized Approach for MMD Two-Sample Tests

arXiv:2605.06883v1 Announce Type: cross Abstract: The Maximum Mean Discrepancy (MMD) is a cornerstone statistic for nonparametric two-sample testing, but its test power is dictated entirely by the cho

Kimi K2.6 was a hit during the launch promotion - so it's staying free for Pro, Teams, and Max users for another month. Enjoy!

Kimi K2.6 was a hit during the launch promotion - so it's staying free for Pro, Teams, and Max users for another month. Enjoy! Kimi K2.6 is now available in Windsurf! Available for free for the next 2

agentscognition-ai--x

Tools

Kimi K2.6 was a hit during the launch promotion - so it's staying free for Pro, Teams, and Max users for another month. Enjoy!

KL for a KL: On-Policy Distillation with Control Variate Baseline

arXiv:2605.07865v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) has emerged as a dominant post-training paradigm for large language models, especially for reasoning domains. However, OP

safetyarxiv-cs-ai

Knowing but Not Correcting: Routine Task Requests Suppress Factual Correction in LLMs

model-releasesarxiv-cs-lg

arXiv:2605.05957v2 Announce Type: replace Abstract: LLMs reliably correct false claims when presented in isolation, yet when the same claims are embedded in task-oriented requests, they often comply r

Knowledge Transfer Scaling Laws for 3D Medical Imaging

arXiv:2605.06859v1 Announce Type: cross Abstract: Vision foundation models are increasingly moving beyond 2D to volumetric domains such as 3D medical imaging, where unified pretraining across differen

Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting

arXiv:2602.02832v3 Announce Type: replace Abstract: Forecasting physical systems over long horizons from irregularly sampled observations demands models that are stable, computationally efficient, and

Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection

arXiv:2605.06955v1 Announce Type: cross Abstract: Denoising score matching (DSM) provides a way to learn data distributions by training a neural network to recover the score function, defined as the g

local-aiarxiv-cs-ai

Applications

LAMES: A Large-Scale and Artisanal Mining Environmental Segmentation Dataset

arXiv:2605.07740v1 Announce Type: new Abstract: Mining operations are of utmost importance to the economy of some nations. However, such operations result in land-use change, very high energy consumpt

applicationsarxiv-cs-cv

LangSmith settling the CLI vs MCP debate by simply offering both

LangSmith settling the CLI vs MCP debate by simply offering both LangSmith is now a remote MCP server. Point any MCP-capable client at it, sign in with your LangSmith account, and your assistant can r

agentsharrison-chase--x

LARAG: Link-Aware Retrieval Strategy for RAG Systems in Hyperlinked Technical Documentation

model-releasesarxiv-cs-ai

arXiv:2605.07517v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances the factual grounding of Large Language Models by conditioning their outputs on external documents. Howe

Applications

Large Video Planner Enables Generalizable Robot Control

arXiv:2512.15840v2 Announce Type: replace-cross Abstract: General-purpose robots require decision-making models that generalize across diverse tasks and environments. Recent works build robot foundati

applicationsarxiv-cs-cv

Last week, the United States refused to participate in the UN’s review of the Global Compact on Migration. The United States objects to the …

Last week, the United States refused to participate in the UN’s review of the Global Compact on Migration. The United States objects to the Global Compact on Migration and UN efforts to facilitate rep

industryelon-musk--x

Latent Order Bandits

arXiv:2605.07304v1 Announce Type: new Abstract: Bandit algorithms solve diverse sequential decision-making problems, but are often too sample-inefficient for from-scratch personalization. To substanti

Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models

arXiv:2602.01166v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models benefit from chain-of-thought (CoT) reasoning, but existing approaches incur high inference overhead and rely on

researcharxiv-cs-ro

Latent-Space Causal Discovery from Indirect Neuroimaging Observations

arXiv:2602.09034v2 Announce Type: replace-cross Abstract: Neuroimaging does not observe causal variables directly: hemodynamics and volume conduction distort signals so that statistical dependence nee

LaTER: Efficient Test-Time Reasoning via Latent Exploration and Explicit Verification

arXiv:2605.07315v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves large language models (LLMs) on difficult tasks, but it also makes inference expensive because every intermedi

researcharxiv-cs-cl

Launch rehearsal complete. During a flight-like countdown, more than 5,000 metric tonnes (11+ million pounds) of propellant were loaded on t…

Launch rehearsal complete. During a flight-like countdown, more than 5,000 metric tonnes (11+ million pounds) of propellant were loaded on the fully stacked Starship and Super Heavy V3 vehicles for th

industryelon-musk--x

Learned Lagrangian Models of PDEs via Euler-Lagrange Residual Minimization

arXiv:2605.07157v1 Announce Type: new Abstract: We present the first method to directly use a learned continuous Lagrangian to forecast the dynamics of systems governed by partial differential equatio

local-aiarxiv-cs-lg

Learned Lyapunov Shielding for Adaptive Control

arXiv:2605.06934v1 Announce Type: new Abstract: We augment the Slotine--Li adaptive controller for Euler--Lagrange systems with three learned components: a structured-quadratic Lyapunov function (V_ps

safetyarxiv-cs-lg

Learning Agent Routing From Early Experience

model-releasesarxiv-cs-cl

arXiv:2605.07180v1 Announce Type: new Abstract: LLM agents achieve strong performance on complex reasoning tasks but incur high latency and compute cost. In practice, many queries fall within the capa

Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents

model-releasesarxiv-cs-ai

arXiv:2605.06957v1 Announce Type: new Abstract: We present a dynamic policy-learning approach that combines generalized planning and hierarchical task decomposition for LLM-based agents. Our method, H

Learning CLI Agents with Structured Action Credit under Selective Observation

arXiv:2605.08013v1 Announce Type: new Abstract: Command line interface (CLI) agents are emerging as a practical paradigm for agent-computer interaction over evolving filesystems, executable command li

agentsarxiv-cs-ai

Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning

arXiv:2605.07026v1 Announce Type: cross Abstract: Functional connectivity (FC) derived from resting-state fMRI is widely used to characterize large-scale brain network alterations in neurological and

safetyarxiv-cs-ai

Learning Image-Adaptive Scale Fields for Metric Depth Recovery

arXiv:2605.07418v1 Announce Type: new Abstract: Monocular depth estimation (MDE) typically produces depth estimations that are defined up to an unknown scale or shift. When only sparse metric anchors

researcharxiv-cs-cv

Tutorials

Learning Large-Scale Modular Addition with an Auxiliary Modulus

arXiv:2605.07648v1 Announce Type: new Abstract: Learning parity functions, more general modular addition, is a challenging machine learning task due to its input sensitivity. A recent study substantia

tutorialsarxiv-cs-lg

Learning Material-Aware Hamiltonian Risk Fields for Safe Navigation

model-releasesarxiv-cs-lg

arXiv:2605.07038v1 Announce Type: new Abstract: Risk-aware navigation should be selective: a policy should expose evasive degrees of freedom only when the local scene admits a lower-risk feasible mane

Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations

arXiv:2605.07460v1 Announce Type: new Abstract: Accurate Monte Carlo (MC) modelling in high-energy physics is challenging, particularly in complex scenarios where simulations fail to reproduce observe

Learning Multi-Relational Graph Representations for DNA Methylation-Based Biological Age Estimation

arXiv:2605.07175v1 Announce Type: cross Abstract: Aging clocks aim to estimate biological age, a measure of physiological state distinct from chronological age, from observable biomarkers, and are wid

local-aiarxiv-cs-ai

Learning on the Shop floor

Learning on the Shop floor Tobias Lütke describes Shopify's internal coding agent tool, River, which operates entirely in public on their Slack: River does not respond to direct messages. She politely

agentssimon-willison

Tutorials

Learning quantum Hamiltonians at any temperature in polynomial time

arXiv:2310.02243v2 Announce Type: replace-cross Abstract: We study the problem of learning a local quantum Hamiltonian H given copies of its Gibbs state rho = e^{-eta H}/extrm{tr}(e^{-eta H}) at a kno

tutorialsarxiv-cs-lg

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding

arXiv:2605.07637v1 Announce Type: new Abstract: Multi-agent pathfinding (MAPF) is a widely used abstraction for multi-robot trajectory planning problems, where multiple homogeneous agents move simulta

local-aiarxiv-cs-ai

Learning to Pose Problems: Reasoning-Driven and Solver-Adaptive Data Synthesis

arXiv:2511.09907v5 Announce Type: replace Abstract: Data synthesis for training large reasoning models offers a scalable alternative to limited, human-curated datasets, enabling the creation of high-q

Learning to Track Instance from Single Nature Language Description

arXiv:2605.07064v1 Announce Type: new Abstract: How to achieve vision-language (VL) tracking using natural language descriptions from a video sequence extbf{without relying on any bounding-box ground

safetyarxiv-cs-cv

Learning Visual Feature-Based World Models via Residual Latent Action

arXiv:2605.07079v1 Announce Type: cross Abstract: World models predict future transitions from observations and actions. Existing works predominantly focus on image generation only. Visual feature-bas

safetyarxiv-cs-ai

Legitimately feels like an unquantifiable vibe shift the last few weeks where the pendulum is swinging back to reasonable takes and people e…

I can see this appears to be a social media post about a perceived shift in online discourse or cultural sentiment, but the truncated title and unavailable URL prevent me from accessing the full conte

industryclem-delangue--x

LENS: Low-Frequency Eigen Noise Shaping for Efficient Diffusion Sampling

arXiv:2605.07253v1 Announce Type: new Abstract: Distilled diffusion models accelerate image generation by reducing the number of denoising steps, but often suffer from degraded image quality. To mitig

researcharxiv-cs-cv

LensVLM: Selective Context Expansion for Compressed Visual Representation of Text

arXiv:2605.07019v1 Announce Type: cross Abstract: Vision Language Models (VLMs) offer the exciting possibility of processing text as rendered images, bypassing the need for tokenizing the text into lo

Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD?

arXiv:2605.07072v1 Announce Type: new Abstract: Poisson subsampling is the default sampling scheme in differentially private machine learning, largely because its unstructured randomness yields tracta

Lightweight Unpaired Smartphone ISP Transfer with Semantic Pseudo-Pairing

arXiv:2605.07495v1 Announce Type: new Abstract: Unpaired smartphone ISP is a challenging problem due to the lack of scene and color alignment between RAW and target RGB images. Many existing methods e

safetyarxiv-cs-cv

Limitations on Accurate, Trusted, Human-level Reasoning

arXiv:2509.21654v2 Announce Type: replace-cross Abstract: We identify a fundamental incompatibility between the goals of accuracy, trust, and human-level reasoning in artificial intelligence (AI) syst