All entries

iReasoner: Trajectory-Aware Intrinsic Reasoning Supervision for Self-Evolving Large Multimodal Models

arXiv:2601.05877v3 Announce Type: replace Abstract: Recent work shows that large multimodal models (LMMs) can self-improve from unlabeled data via self-play and intrinsic feedback. Yet existing self-e

Applications

Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning

DGX agent

arXiv:2605.21475v1 Announce Type: new Abstract: Relational prediction tasks are fundamental in many real-world applications, where data are naturally stored in relational databases (RDBs). Relational

applicationsarxiv-cs-lg

21 May 2026

It is the answer

It is the answer This was my favorite moment from Elon, Franz, and Lars yesterday. Elon: 'I’ll tell you something, maybe at a fundamental level why the Model S/X succeeded, which is that, those cars w

industryelon-musk--x

It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs

arXiv:2605.20258v1 Announce Type: new Abstract: Contextual Integrity (CI) defines privacy not merely as keeping information hidden, but as governing information flows according to the norms of a given

safetyarxiv-cs-lg

Tools

It was an honor to give the keynote at MLSys Covered how AI systems have evolved, why AI is needed to improve them, why results have disappo…

It was an honor to give the keynote at MLSys Covered how AI systems have evolved, why AI is needed to improve them, why results have disappointed, why the future looks amazing, and why I’m working on

toolsswyx--x

Iterative LLM-based improvement for French Clinical Interview Transcription and Speaker Diarization

arXiv:2603.00086v2 Announce Type: replace Abstract: Automatic speech recognition for French medical conversations remains challenging, with word error rates often exceeding 30% in spontaneous clinical

iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance

arXiv:2605.21431v1 Announce Type: new Abstract: Video Virtual Try-On (VVT) aims to seamlessly replace a garment on a person in a video with a new one. While existing methods have made significant stri

tutorialsarxiv-cs-cv

It’s crazy that OpenAI and xAI were built partly as ways to mitigate @demishassabis’s power and how both are more reckless and less focused …

It’s crazy that OpenAI and xAI were built partly as ways to mitigate @demishassabis’s power and how both are more reckless and less focused on the good part, viz AI for science. And then Anthropic was

safetygary-marcus--x

It’s pronounced “Hermes”, not “Hermes”

This post likely clarifies the correct pronunciation of 'Hermes' (the Greek mythological messenger god and luxury brand), humorously highlighting a common mispronunciation among English speakers. The

researchnous-research--x

Japan’s AI adoption growth is remarkable. In just a few days here, you can already see how different the perceptions around adoption and use…

industrycristobal-valenzuela--x

Japan’s AI adoption growth is remarkable. In just a few days here, you can already see how different the perceptions around adoption and use cases are. Also, I love seeing books about Runway. Country-

Jeff Bezos dismisses AI job fears, defends billionaires against 'vilification', proposes eliminating income taxes for low earners, and praises President Trump (CNBC)

CNBC: Jeff Bezos dismisses AI job fears, defends billionaires against “vilification”, proposes eliminating income taxes for low earners, and praises President Trump — VIDEO 54:38 — Watch CNBC's full i

industrytechmeme

JFAA: Technical Report for the EPIC-KITCHENS-100 Action Anticipation Challenge at EgoVis 2026

arXiv:2605.20904v1 Announce Type: new Abstract: We propose JFAA, a JEPA-based Future Action Anticipation method for the EPIC-KITCHENS-100 (EK-100) Action Anticipation task. Inspired by the representat

JobArabi: An Arabic Corpus and Analysis of Job Announcements from Social Media

arXiv:2605.20960v1 Announce Type: new Abstract: This paper introduces JobArabi, a large-scale corpus of Arabic job announcements collected from social media between January 2024 and October 2025. The

Jointly Learning Predicates and Actions Enables Zero-Shot Skill Composition

arXiv:2605.20648v1 Announce Type: new Abstract: Learning from Demonstration (LfD) enables robots to learn complex behaviors from expert examples, yet existing approaches often fail to generalize to ne

tutorialsarxiv-cs-ro

JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA

arXiv:2605.20284v1 Announce Type: new Abstract: Industrial anomaly detection has been significantly advanced by Large Multimodal Models (LMMs), enabling diverse human instructions beyond detection, pa

Hardware

JUST IN: SpaceX pledges to cover all power grid infrastructure upgrade costs associated with its data centers so those costs are not passed …

JUST IN: SpaceX pledges to cover all power grid infrastructure upgrade costs associated with its data centers so those costs are not passed on to local households, per its S-1 filing. JUST IN: COLOSSU

hardwareelon-musk--x

JWST maps the weather on a hot gas giant 700 light-years away

The James Webb Space Telescope has created the first weather map of the exoplanet WASP-94A b, located nearly 700 light-years from Earth, revealing that morning clouds make way for clear skies at night

industryars-technica

Agents

Kafka, but for agents!

Kafka, but for agents! i'm excited to open source Active Graph: an event-sourced reactive graph runtime for long-running, agents 🔄🧠 events/logs projects a graph. reactive behaviors react and affect th

agentsyohei-nakajima--x

LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models

arXiv:2506.16950v2 Announce Type: replace Abstract: Out-of-distribution (OOD) robustness is a desired property of computer vision models. Improving model robustness requires high-quality signals from

Hardware

Lambda Bare Metal Instances: full hardware control with API-driven operations

The unit of AI compute has shifted from single hosts to rack-scale systems that integrate NVIDIA GPUs, CPUs, scale-up networking fabrics, and liquid cooling, such as the NVIDIA GB300 NVL72 and NVIDIA

hardwarelambda-labs

LamPO: A Lambda Style Policy Optimization for Reasoning Language Models

arXiv:2605.21235v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving reasoning language models on tasks such as mathemat

Large Language Models Unpack Complex Political Opinions through Target-Stance Extraction

arXiv:2603.23531v2 Announce Type: replace Abstract: Political polarization emerges from a complex interplay of beliefs about policies, figures, and issues. However, most computational analyses reduce

Large-Step Training Dynamics of a Two-Factor Linear Transformer Model

arXiv:2605.21292v1 Announce Type: cross Abstract: Gradient-flow analyses show that simplified linear transformers can learn the in-context linear-regression algorithm, but they do not explain the fini

LASH: Adaptive Semantic Hybridization for Black-Box Jailbreaking of Large Language Models

arXiv:2605.21362v1 Announce Type: new Abstract: Jailbreak attacks expose a persistent gap between the intended safety behavior of aligned large language models and their behavior under adversarial pro

safetyarxiv-cs-cl

Latent Dynamics for Full Body Avatar Animation

arXiv:2605.21478v1 Announce Type: new Abstract: Pose-driven full-body avatars built on neural rendering produce high-quality novel views of a captured subject. Yet loose clothing and other dynamic ele

researcharxiv-cs-cv

Latent Geometry as a Structural Monitor: Eigenspace Alignment for Anomaly Detection in Anonymity Networks

arXiv:2605.20391v1 Announce Type: cross Abstract: Traditional anomaly detection marks events when measured signals cross predefined thresholds. This captures the moment of transition but not the struc

safetyarxiv-cs-lg

Latent Process Generator Matching

arXiv:2605.20547v1 Announce Type: new Abstract: Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to

tutorialsarxiv-cs-lg

Applications

Latent Space Guided Scenario Sampling for Multimodal Segmentation Under Missing Modalities

arXiv:2605.20372v1 Announce Type: new Abstract: Multimodal semantic segmentation benefits remote sensing analysis by combining complementary information from different sensor modalities. In real-world

applicationsarxiv-cs-cv

Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search

arXiv:2605.20244v1 Announce Type: cross Abstract: We present Lean Refactor, a plug-and-play retrieval-augmented agentic framework for multi-objective, controllable, and version-robust refactoring of L

LEAP: A closed-loop framework for perovskite precursor additive discovery

arXiv:2605.20242v1 Announce Type: new Abstract: Efficient discovery of precursor additives is essential for improving the performance of perovskite solar cells, yet the large chemical space makes conv

Learn how to build LLM Wikis and LLM Artifacts.

Learn how to build LLM Wikis and LLM Artifacts. New VIDEO: From LLM Wikis to LLM Artifacts Shared all my thoughts on why LLM wikis and HTML artifacts are a big deal. Plus, new tools to help you build

tutorialsdair-ai--x

Learn more about Replit Enterprise here: https://replit.com/enterprise

Replit Enterprise is a commercial offering from Replit designed for organizations and businesses seeking advanced collaborative coding and development capabilities on the Replit platform. This likely

tutorialsreplit--x

Applications

Learning Dynamics from Infrequent Output Measurements for Uncertainty-Aware Optimal Control

arXiv:2512.08013v2 Announce Type: replace-cross Abstract: Reliable optimal control is challenging when the dynamics of a nonlinear system are unknown and only infrequent, noisy output measurements are

applicationsarxiv-cs-lg

Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning

arXiv:2605.21160v1 Announce Type: new Abstract: The discovery of first integrals is of fundamental scientific importance for understanding conservation laws in dynamical systems. However, existing sym

researcharxiv-cs-lg

Learning fMRI activations dictionaries across individual geometries via optimal transport

arXiv:2605.20883v1 Announce Type: new Abstract: Dictionary learning is a powerful tool for creating interpretable representations. When applied to functional magnetic resonance imaging (fMRI) data, th

Agents

Learning Incentive Structures for Cooperative Resilience in Multi-Agent Systems under Social Dilemmas

arXiv:2601.22292v2 Announce Type: replace-cross Abstract: Multi-agent social dilemmas, such as the tragedy of the commons, capture settings where individual incentives conflict with collective well-be

agentsarxiv-cs-lg

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

arXiv:2602.06025v2 Announce Type: replace Abstract: Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offl

Learning Robust Dexterous In-Hand Manipulation from Joint Sensors with Proprioceptive Transformer

arXiv:2605.21330v1 Announce Type: new Abstract: In-hand object manipulation is a fundamental yet challenging capability for dexterous robots. Despite significant progress in dexterous manipulation, ex

safetyarxiv-cs-ro

Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation

arXiv:2605.21258v1 Announce Type: new Abstract: Current 3D-aware pretraining methods for embodied perception and manipulation are largely built on differentiable rendering frameworks, producing either

researcharxiv-cs-ro

Learning to Defer in Non-Stationary Time Series via Switching State-Space Models

arXiv:2601.22538v2 Announce Type: replace Abstract: Learning-to-defer (L2D) routes each decision to a system's own predictor or to an external expert. Streaming time-series settings break the offline-

tutorialsarxiv-cs-lg

Learning-to-Defer with Expert-Conditional Advice

arXiv:2603.14324v3 Announce Type: replace-cross Abstract: Learning-to-Defer routes each input to the expert that minimizes expected cost, but it assumes that the information available to every expert

Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment

arXiv:2605.20780v1 Announce Type: cross Abstract: Physics-informed diffusion models typically enforce PDE constraints only on final outputs, leaving intermediate representations unconstrained and pron

safetyarxiv-cs-cv

LER-YOLO: Reliability-Aware Expert Routing for Misaligned RGB-Infrared UAV Detection

arXiv:2605.20667v1 Announce Type: new Abstract: Detecting small unmanned aerial vehicles from RGB-infrared remote-sensing pairs remains challenging due to tiny target scale, cluttered backgrounds, and

Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases

arXiv:2605.20314v1 Announce Type: new Abstract: This work investigates the ``small-vs-large gap'', where repeating on fewer samples can lead to compute saving during training compared to using a large

researcharxiv-cs-lg

Let EEG Models Learn EEG

arXiv:2605.21280v1 Announce Type: new Abstract: High-fidelity EEG generation is critical for alleviating data scarcity and addressing privacy constraints in large-scale neural modeling. Despite recent

tutorialsarxiv-cs-cv

Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching

arXiv:2510.09060v2 Announce Type: replace-cross Abstract: Flow-based text-to-image models follow deterministic trajectories, making it costly to explore diverse modes under limited sampling budgets. E

safetyarxiv-cs-cv

Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

arXiv:2605.20192v1 Announce Type: new Abstract: Decentraland, a decentralized virtual reality platform operating within the expanding Metaverse ecosystem, utilizes its native MANA token to facilitate

Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution

arXiv:2605.21465v1 Announce Type: new Abstract: In model-driven engineering, metamodel evolution leads to the need to adapt corresponding grammars to maintain consistency, which typically requires ted