All entries

Leveraging Multimodal Large Language Models for All-in-One Image Restoration via a Mixture of Frequency Experts

arXiv:2605.11444v1 Announce Type: new Abstract: All-in-one image restoration seeks to recover clean images from inputs affected by diverse and unknown degradations using a unified framework. Recent me

Leveraging RAG for Training-Free Alignment of LLMs

DGX agent

arXiv:2605.11217v1 Announce Type: new Abstract: Large language model (LLM) alignment algorithms typically consist of post-training over preference pairs. While such algorithms are widely used to enabl

safetyarxiv-cs-lg

13 May 2026

LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection

arXiv:2605.11231v1 Announce Type: new Abstract: Synthetic data is useful only when the added samples fill missing parts of the training distribution that matter for the downstream task. We introduce L

LiBrA-Net: Lie-Algebraic Bilateral Affine Fields for Real-Time 4K Video Dehazing

model-releasesarxiv-cs-cv

arXiv:2605.11508v1 Announce Type: new Abstract: Currently, there is a gap in the field of ultra-high-definition (UHD) video dehazing due to the lack of a benchmark for evaluation. Furthermore, existin

Limits of Learning Linear Dynamics from Experiments

arXiv:2605.12010v1 Announce Type: new Abstract: Learning governing dynamics from data is a common goal across the sciences, yet it is only well-posed when the underlying mechanisms are identifiable. I

Industry

LinkedIn says it has 'implemented organizational changes'; a source says LinkedIn plans to cut about 5% of its 17,500 full-time workers (Reuters)

Reuters: LinkedIn says it has “implemented organizational changes”; a source says LinkedIn plans to cut about 5% of its 17,500 full-time workers — LinkedIn planned to inform staff of layoffs on Wednes

industrytechmeme

Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.11354v1 Announce Type: new Abstract: Transformer-based 3D reconstruction has emerged as a powerful paradigm for recovering geometry and appearance from multi-view observations, offering str

literally what i have been saying for years, once again.

literally what i have been saying for years, once again. Yann LeCun says you cannot build a reliable agentic system without a world model LLMs don't have world models. They can't predict the consequen

agentsgary-marcus--x

Tools

Live From SaaStr: Midday on the Floor (Day 2) https://x.com/i/broadcasts/1qxoNeyVmwbJv

This was a live broadcast from SaaStr (a SaaS industry conference), streamed on X by Replit on Day 2 of the event. The 'Midday on the Floor' segment likely featured live updates, interviews, or discus

toolsreplit--x

Local and Mixing-Based Algorithms for Gaussian Graphical Model Selection from Glauber Dynamics

arXiv:2412.18594v3 Announce Type: replace Abstract: Gaussian graphical model selection is usually studied under independent sampling, but in many applications observations arise from dependent dynamic

local-aiarxiv-cs-lg

Localising Dropout Variance in Twin Networks

arXiv:2507.03622v2 Announce Type: replace Abstract: Accurate individual treatment-effect estimation demands not only reliable point predictions but also uncertainty measures that help practitioners lo

applicationsarxiv-cs-lg

Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank

arXiv:2605.11272v1 Announce Type: new Abstract: Adobe Express is expanding internationally, but the US has a disproportionately large content supply and interaction volume. Learning-to-rank (LTR) mode

local-aiarxiv-cs-lg

LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection

model-releasesarxiv-cs-lg

arXiv:2605.11872v1 Announce Type: new Abstract: Orthogonal parameter-efficient fine-tuning (PEFT) adapts pretrained weights through structure-preserving multiplicative transformations, but existing me

Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration

arXiv:2605.11591v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in multi-image cross-modal retrieval, yet suffer from severe position bias, where

Long Story Short: Disentangling Compositionality and Long-Caption Understanding in Contrastive VLMs

model-releasesarxiv-cs-cv

arXiv:2509.19207v2 Announce Type: replace Abstract: Contrastive vision-language models (VLMs) have made significant progress in binding visual and textual information, yet understanding long, composit

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues

model-releasesarxiv-cs-cl

arXiv:2605.12493v1 Announce Type: new Abstract: Long-term memory is crucial for agents in specialized web environments, where success depends on recalling interface affordances, state dynamics, workfl

Looking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-Making

arXiv:2602.07668v2 Announce Type: replace Abstract: The looking-in-looking-out (LILO) framework has enabled intelligent vehicle applications that understand both the outside scene and the driver state

looks like http://di.gg expanded their rankings beyond 1000 little me is ranked #1556 and auto-classified as an engineer 🤷‍♂️

Digg expanded its ranking system beyond the top 1000 users, with Yohei Nakajima noting he was ranked #1556 and automatically classified as an engineer in the expanded rankings. The post reflects on th

agentsyohei-nakajima--x

LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models

arXiv:2605.11011v1 Announce Type: new Abstract: Looped computation shows promise in improving the reasoning-oriented performance of LLMs by scaling test-time compute. However, existing approaches typi

Lower bounds for one-layer transformers that compute parity

arXiv:2605.12171v1 Announce Type: new Abstract: This note shows that no self-attention layer post-processed by a rational function can sign-represent the parity function unless the product of the numb

LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows

arXiv:2605.11368v1 Announce Type: new Abstract: We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation fr

local-aiarxiv-cs-lg

LTX 2.3 INT8 Benchmarks (2x Faster on Ampere)

local-air-stablediffusion

LTX-2.3 INT8 benchmarks discuss INT8 quantization optimized for Ampere GPUs (RTX 30XX series), which offers a balance between speed, VRAM usage, and quality. These INT8 models are designed to speed up

LTX 2.3 Outpaint causes blurry Faces

local-air-stablediffusion

LTX 2.3 Outpaint is a tool that extends video canvas by generating new content in marked regions while maintaining visual and temporal consistency with the original footage. Users in the r/StableDiffu

LucidFlux: Caption-Free Photo-Realistic Image Restoration via a Large-Scale Diffusion Transformer

arXiv:2509.22414v4 Announce Type: replace Abstract: Image restoration (IR) aims to recover images degraded by unknown mixtures while preserving semanticsconditions under which discriminative restorers

LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Flow-Based Real-World Super-Resolution

arXiv:2603.05947v3 Announce Type: replace Abstract: Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details from severely degraded low-resolution (LR) inputs

LychSim: A Controllable and Interactive Simulation Framework for Vision Research

arXiv:2605.12449v1 Announce Type: new Abstract: While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optim

agentsarxiv-cs-cv

M^4-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection

arXiv:2605.11760v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM

applicationsarxiv-cs-cv

MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making

arXiv:2507.21159v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have proven effective in artificial intelligence, where the multi-agent system (MAS) holds considerable promise f

agentsarxiv-cs-lg

Machine Learning for neutron source distributions

arXiv:2605.12165v1 Announce Type: cross Abstract: In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation

MajinBook: An open catalogue of digitally mediated world literature

arXiv:2511.11412v5 Announce Type: replace Abstract: This data paper introduces MajinBook, an open catalogue designed to facilitate the use of shadow libraries-such as Library Genesis and Z-Library-for

safetyarxiv-cs-cl

Make It Long, Keep It Fast: End-to-End 10k-Sequence Modeling at Billion Scale on Douyin Recommendation

arXiv:2511.06077v2 Announce Type: replace Abstract: Short-video recommenders such as Douyin must exploit extremely long user histories without breaking latency or cost budgets. We present an end-to-en

applicationsarxiv-cs-lg

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining

arXiv:2605.11034v1 Announce Type: cross Abstract: We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In con

Manifold Sampling via Entropy Maximization

arXiv:2605.12338v1 Announce Type: new Abstract: Sampling from constrained distributions has a wide range of applications, including in Bayesian optimization and robotics. Prior work establishes conver

Mapping Embodied Affective Touch Strategies on a Humanoid Robot

arXiv:2605.11825v1 Announce Type: new Abstract: Affective touch in human-robot interaction is shaped not only by emotional intent, but also by robot embodiment, including touch location, physical cons

researcharxiv-cs-ro

Industry

Mark Zuckerberg announces ‘completely private’ encrypted Meta AI chat

Meta CEO Mark Zuckerberg says its new Incognito Chat is 'the first major AI product where there is no log of your conversations stored on servers.' Messages in Incognito Chat aren't saved or stored in

industrythe-verge-ai

Martingale-Consistent Self-Supervised Learning

arXiv:2605.11846v1 Announce Type: new Abstract: Self-supervised learning (SSL) is often deployed under changing information, such as shorter histories, missing features, or partially observed images.

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification

arXiv:2605.11408v1 Announce Type: cross Abstract: Tabular data forms the backbone of high-stakes decision systems in finance, healthcare, and beyond. Yet industrial tabular datasets are inherently dif

applicationsarxiv-cs-cl

Maximin Robust Bayesian Experimental Design

arXiv:2603.14094v2 Announce Type: replace-cross Abstract: We address the brittleness of Bayesian experimental design under model misspecification by formulating the problem as a max--min game between

safetyarxiv-cs-lg

MCPShield: Content-Aware Attack Detection for LLM Agent Tool-Call Traffic

arXiv:2605.11053v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become a widely adopted interface for LLM agents to invoke external tools, yet learned monitoring of MCP tool-cal

agentsarxiv-cs-lg

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models

arXiv:2605.02798v1 Announce Type: cross Abstract: We present an experimental study of energy-to-solution (ETS) of hybrid quantum-classical applications, enabled by direct instrumentation of power cons

applicationsarxiv-cs-lg

Measuring Five-Nines Reliability: Sample-Efficient LLM Evaluation in Saturated Benchmarks

model-releasesarxiv-cs-lg

arXiv:2605.11209v1 Announce Type: new Abstract: While existing benchmarks demonstrate the near-perfect performance of large language models (LLMs) on various tasks, this apparent saturation often obsc

Mechanistic Interpretability of ASR models using Sparse Autoencoders

arXiv:2605.12225v1 Announce Type: new Abstract: Understanding the internal machinations of deep Transformer-based NLP models is more crucial than ever as these models see widespread use in various dom

applicationsarxiv-cs-cl

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

model-releasesarxiv-cs-cl

arXiv:2605.12361v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain dis

Meet Runway Agent. Your new AI creative partner that helps you ideate and execute fully finished, sound designed and edited videos. All with…

agentscristobal-valenzuela--x

Meet Runway Agent. Your new AI creative partner that helps you ideate and execute fully finished, sound designed and edited videos. All with just a simple conversation. From ads to shorts to content f

Tutorials

// δ-mem: Efficient Online Memory for LLMs // One of the more elegant memory mechanisms I've seen this month. Most long-term memory work eit…

// δ-mem: Efficient Online Memory for LLMs // One of the more elegant memory mechanisms I've seen this month. Most long-term memory work either inflates context or retrains the model. This paper shows

tutorialsdair-ai--x

MEME: Multi-entity & Evolving Memory Evaluation

model-releasesarxiv-cs-cl

arXiv:2605.12477v1 Announce Type: cross Abstract: LLM-based agents increasingly operate in persistent environments where they must store, update, and reason over information across many sessions. Whil

MetaColloc: Optimization-Free PDE Solving via Meta-Learned Basis Functions

arXiv:2605.12368v1 Announce Type: new Abstract: Solving partial differential equations (PDEs) with machine learning typically requires training a new neural network for every new equation. This optimi

Metaphor Is Not All Attention Needs

arXiv:2605.12128v1 Announce Type: new Abstract: Large language models are increasingly deployed in safety-critical applications, where their ability to resist harmful instructions is essential. Althou

safetyarxiv-cs-cl