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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

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Industry

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

DGX agent

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

11 May 2026

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

Linear Response Estimators for Singular Statistical Models

arXiv:2605.07970v1 Announce Type: cross Abstract: We define susceptibilities as a measure of the response of an observable quantity of a parameterized statistical model to a perturbation of the data f

Linux bitten by second severe vulnerability in as many weeks

In April 2026, researchers disclosed CVE-2026-31431 ('Copy Fail'), a highly reliable local privilege escalation vulnerability allowing unprivileged attackers to escalate to root across virtually all m

applicationsars-technica

Local Ai

LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning

arXiv:2605.07505v1 Announce Type: new Abstract: Developing lightweight, on-device vision-language GUI agents is essential for efficient cross-platform automated interaction. However, current on-device

local-aiarxiv-cs-ai

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation

arXiv:2605.07640v1 Announce Type: cross Abstract: Remote sensing lithology interpretation is fundamental to geological surveys, mineral exploration, and regional geological mapping. Unlike general lan

LKV: End-to-End Learning of Head-wise Budgets and Token Selection for LLM KV Cache Eviction

arXiv:2605.06676v1 Announce Type: cross Abstract: Long-context inference in Large Language Models (LLMs) is bottlenecked by the linear growth of Key-Value (KV) cache memory. Existing KV cache compress

tutorialsarxiv-cs-cl

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

arXiv:2508.16571v4 Announce Type: replace Abstract: In this paper, we describe and benchmark a competitor-discovery component used within an agentic AI system for fast drug asset due diligence. A comp

LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments

arXiv:2605.06839v1 Announce Type: cross Abstract: Autonomous experimentation has transformed microscopy and materials discovery by enabling closed-loop optimization including imaging and spectroscopy

agentsarxiv-cs-ai

LLM hallucinations in the wild: Large-scale evidence from non-existent citations

arXiv:2605.07723v1 Announce Type: cross Abstract: Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and c

applicationsarxiv-cs-ai

LLMs are not (consistently) Bayesian: Quantifying internal (in)consistencies of LLMs' probabilistic beliefs

arXiv:2605.06915v1 Announce Type: new Abstract: Modern AI systems are being deployed in complex domains such as medicine, science, and law, where it is important that they not only produce correct ans

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling

arXiv:2605.08083v1 Announce Type: new Abstract: Test-time scaling (TTS) has become an effective approach for improving large language model performance by allocating additional computation during infe

agentsarxiv-cs-cl

// LLMs Improving LLMs // Interesting progress the past of couple of weeks around self-improving AI agents. If autoresearch was interesting,…

// LLMs Improving LLMs // Interesting progress the past of couple of weeks around self-improving AI agents. If autoresearch was interesting, you will like this read. (bookmark it) We've been hand-tuni

tutorialsdair-ai--x

Hardware

LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites

arXiv:2605.05615v2 Announce Type: replace Abstract: Large language models (LLMs) impose rapidly growing energy demands, creating an emerging energy and carbon crisis driven by large-scale inference. S

hardwarearxiv-cs-lg

Local open-weight AI on a laptop has been improving more than twice as fast as Moore's Law! Between May 2024 and May 2026, the most expensiv…

model-releasesclem-delangue--x

Local open-weight AI on a laptop has been improving more than twice as fast as Moore's Law! Between May 2024 and May 2026, the most expensive MacBook Pro you could buy stayed at 128 GB of unified memo

Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions

arXiv:2605.06959v1 Announce Type: cross Abstract: This paper presents a parametric solution to piecewise linear regression through the Adaptive Block Gradient Descent (ABGD) algorithm. The heart of th

applicationsarxiv-cs-lg

Local Ai

LoHGNet: Infrared Small Target Detection through Lorentz Geometric Encoding with High-Order Relation Learning

arXiv:2605.07213v1 Announce Type: new Abstract: Infrared small target detection (IRSTD) remains challenging due to the scarcity of useful target cues and the presence of severe background clutter. Mos

local-aiarxiv-cs-cv

Industry

Look who’s just arrived! Reachy Mini Wireless! 🚀

Reachy Mini Wireless is a new robotic product announcement, likely featuring wireless connectivity capabilities and representing an advancement in the Reachy robot line. The announcement was made by C

industryclem-delangue--x

LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute

arXiv:2605.06809v1 Announce Type: new Abstract: Transformers dominate video recognition. They split videos into tokens, and processing them has expensive superlinear computational cost. Yet videos are

tutorialsarxiv-cs-cv

Lossy Common Information in a Learnable Gray-Wyner Network

arXiv:2601.21424v3 Announce Type: replace-cross Abstract: Many computer vision tasks share substantial overlapping information, yet conventional codecs tend to ignore this, leading to redundant and in

researcharxiv-cs-cv

Tools

lowkey the funniest videos of the batch. thinky has some comedians!! congrats to @thinkymachines on reviving the omnimodel dream that others…

lowkey the funniest videos of the batch. thinky has some comedians!! congrats to @thinkymachines on reviving the omnimodel dream that others could not Today we're sharing our work on interaction model

toolsswyx--x

LR-SGS: Robust LiDAR-Reflectance-Guided Salient Gaussian Splatting for Self-Driving Scene Reconstruction

arXiv:2603.12647v2 Announce Type: replace-cross Abstract: Recent 3D Gaussian Splatting (3DGS) methods have demonstrated the feasibility of self-driving scene reconstruction and novel view synthesis. H

Local Ai

LTX 2.3 Distilled 1.1 using WwnGP.

local-air-stablediffusion

LTX-2.3 is a multimodal video generation model released by Lightricks in March 2026, available in four checkpoint variants including a distilled variant that completes generation in as few as 8 denois

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference

arXiv:2605.05225v2 Announce Type: replace-cross Abstract: Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant efficiency bottleneck during Expert Parallelism (EP)

Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate

arXiv:2605.07342v1 Announce Type: cross Abstract: Compile-pass rate is the dominant evaluation signal for LLM code generation, yet for multi-component domain-specific artifacts it can be actively misl

MAGIQ: A Post-Quantum Multi-Agentic AI Governance System with Provable Security

arXiv:2605.06933v1 Announce Type: new Abstract: Our computing ecosystem is being transformed by two emerging paradigms: the increased deployment of agentic AI systems and advancements in quantum compu

safetyarxiv-cs-lg

Making AI Evaluation Deployment Relevant Through Context Specification

arXiv:2603.06811v3 Announce Type: replace Abstract: With many organizations struggling to gain value from AI deployments, pressure to evaluate AI in an informed manner has intensified. Status quo AI e

Manifold Random Features

arXiv:2602.03797v2 Announce Type: replace Abstract: We present a new paradigm for creating random features to approximate bi-variate functions (in particular, kernels) defined on general manifolds. Th

tutorialsarxiv-cs-lg

Manufacturing intelligence with Amazon Nova Multimodal Embeddings

In this post, we build a multimodal retrieval system for aerospace manufacturing documents using Amazon Nova Multimodal Embeddings on Amazon Bedrock and Amazon S3 Vectors. We evaluate the system on 26

applicationsaws-ml-blog

Many-to-Many Multi-Agent Pickup and Delivery

arXiv:2605.07835v1 Announce Type: new Abstract: Multi-robot systems in automated warehouses must manage continuous streams of pickup-and-delivery tasks while ensuring efficiency and safety. Prior work

safetyarxiv-cs-ro

MaPPO: Maximum a Posteriori Preference Optimization with Prior Knowledge

arXiv:2507.21183v5 Announce Type: replace-cross Abstract: As the era of large language models (LLMs) unfolds, Preference Optimization (PO) methods have become a central approach to aligning LLMs with

safetyarxiv-cs-ai

MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System

arXiv:2605.05949v2 Announce Type: replace Abstract: Algorithmic problem solving serves as a rigorous testbed for evaluating structured reasoning in AI coding systems, as it directly reflects a model's

Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention

arXiv:2605.07280v1 Announce Type: cross Abstract: Leveraging deep learning for causal discovery in time series remains challenging because existing neural methods predominantly rely on component-wise

Masks Can Talk: Extracting Structured Text Information from Single-Modal Images for Remote Sensing Change Detection

arXiv:2605.07178v1 Announce Type: new Abstract: Remote sensing change detection is pivotal for urban monitoring, disaster assessment, and environmental resource management. Yet, unimodal deep learning

safetyarxiv-cs-cv

MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems

arXiv:2605.06623v1 Announce Type: cross Abstract: Large language model (LLM)-based Multi-agent systems (MAS) have shown promise in tackling complex collaborative tasks, where agents are typically orch

agentsarxiv-cs-lg

MAST: A Multi-fidelity Augmented Surrogate model via Spatial Trust-weighting

arXiv:2602.20974v2 Announce Type: replace Abstract: In engineering design and scientific computing, computational cost and predictive accuracy are intrinsically coupled. High-fidelity simulations prov

Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators

arXiv:2605.07600v1 Announce Type: cross Abstract: Recent methods for improving LLM mathematical reasoning, whether through MCTS-based test-time search or causal graph-guided knowledge injection, canno

MathlibPR: Pull Request Merge-Readiness Benchmark for Formal Mathematical Libraries

arXiv:2605.07147v1 Announce Type: cross Abstract: The ecosystem of Lean and Mathlib has become the de facto standard for large language model (LLM) assisted formal reasoning with remarkable successes

mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments

arXiv:2605.07841v1 Announce Type: cross Abstract: Decentralized machine learning often relies on outsourcing computations, such as gradient evaluations, to untrusted worker nodes. Existing robust aggr

agentsarxiv-cs-ai

MatryoshkaLoRA: Learning Accurate Hierarchical Low-Rank Representations for LLM Fine-Tuning

arXiv:2605.07850v1 Announce Type: cross Abstract: With the rise in scale for deep learning models to billions of parameters, the computational cost of fine-tuning remains a significant barrier to depl

MAVEN: Multi-Agent Verification-Elaboration Network with In-Step Epistemic Auditing

arXiv:2605.07646v1 Announce Type: cross Abstract: While explicit reasoning trajectories enhance model interpretability, existing paradigms often rely on monolithic chains that lack intermediate verifi

Industry

Maye Musk on Elon: He wants to leave the world in a better place than he found it “People often misunderstand Elon. He’s not motivated by mo…

Maye Musk on Elon: He wants to leave the world in a better place than he found it “People often misunderstand Elon. He’s not motivated by money or fame—he’s motivated by the idea of improving humanity

industryelon-musk--x

McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware

model-releasesarxiv-cs-lg

arXiv:2605.06894v1 Announce Type: cross Abstract: Machine learning (ML) in real-world systems must contend with concept drift, adversarial actors, and a spectrum of potential features with varying cos