All entries

Learning Physics from Pretrained Video Models: A Multimodal Continuous and Sequential World Interaction Models for Robotic Manipulation

arXiv:2603.00110v2 Announce Type: replace Abstract: The scarcity of large-scale robotic data has motivated the repurposing of foundation models from other modalities for policy learning. In this work,

safetyarxiv-cs-ro

Local Ai

Learning Reasoning Reward Models from Expert Demonstration via Inverse Reinforcement Learning

DGX agent

arXiv:2510.01857v3 Announce Type: replace Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces o

local-aiarxiv-cs-ai

24 Apr 2026

Learning State-Tracking from Code Using Linear RNNs

arXiv:2602.14814v2 Announce Type: replace-cross Abstract: Over the last years, state-tracking tasks, particularly permutation composition, have become a testbed to understand the limits of sequence mo

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or

Tutorials

Learning to Emulate Chaos: Adversarial Optimal Transport Regularization

arXiv:2604.21097v1 Announce Type: cross Abstract: Chaos arises in many complex dynamical systems, from weather to power grids, but is difficult to accurately model using data-driven emulators, includi

tutorialsarxiv-cs-lg

Let's go DeepSeek v4!!! 🚗🚀

Let's go DeepSeek v4!!! 🚗🚀 DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL

model-releasesollama--x

Leveraging Multimodal LLMs for Built Environment and Housing Attribute Assessment from Street-View Imagery

arXiv:2604.21102v1 Announce Type: cross Abstract: We present a novel framework for automatically evaluating building conditions nationwide in the United States by leveraging large language models (LLM

Linear Image Generation by Synthesizing Exposure Brackets

arXiv:2604.21008v1 Announce Type: new Abstract: The life of a photo begins with photons striking the sensor, whose signals are passed through a sophisticated image signal processing (ISP) pipeline to

researcharxiv-cs-cv

Listen and Chant Before You Read: The Ladder of Beauty in LM Pre-Training

arXiv:2604.21265v1 Announce Type: new Abstract: We show that pre-training a Transformer on music before language significantly accelerates language acquisition. Using piano performances (MAESTRO datas

Listening to startups like @InstalilyAI, @UnslothAI, @splinetool, @ollama, and more talk about how they're using Gemini and Gemma models in …

Listening to startups like @InstalilyAI, @UnslothAI, @splinetool, @ollama, and more talk about how they're using Gemini and Gemma models in production. 🙌🚀 Can't wait for the @garrytan @demishassabis f

model-releasesollama--x

LiveSense: A Real-Time Wi-Fi Sensing Platform for Range-Doppler on COTS Laptop

arXiv:2603.06545v2 Announce Type: replace-cross Abstract: We present LiveSense - a cross-platform that transforms a commercial off-the-shelf (COTS) Wi-Fi Network Interface Card (NIC) on a laptop into

local-aiarxiv-cs-ai

LiveVLM: Efficient Online Video Understanding via Streaming-Oriented KV Cache and Retrieval

model-releasesarxiv-cs-cv

arXiv:2505.15269v2 Announce Type: replace Abstract: Recent developments in Video Large Language Models (Video LLMs) have enabled models to process hour-long videos and exhibit exceptional performance.

LLaDA2.0-Uni Released

model-releasesr-stablediffusion

LLaDA2.0-Uni is a unified diffusion large language model (dLLM) based on Mixture-of-Experts architecture that seamlessly integrates multimodal understanding and generation. The model supports text-to-

llm 0.31

model-releasessimon-willison

Release: llm 0.31 New GPT-5.5 OpenAI model: llm -m gpt-5.5. #1418 New option to set the text verbosity level for GPT-5+ OpenAI models: -o verbosity low. Values are low, medium, high. New option for se

Local Neighborhood Instability in Parametric Projections: Quantitative and Visual Analysis

arXiv:2604.21617v1 Announce Type: new Abstract: Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable s

safetyarxiv-cs-cv

Locating acts of mechanistic reasoning in student team conversations with mechanistic machine learning

arXiv:2604.21870v1 Announce Type: cross Abstract: STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capaci

safetyarxiv-cs-lg

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

arXiv:2505.13527v3 Announce Type: replace-cross Abstract: Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to j

lol these headlines 😅 Btw the meta thing is that he's flying to work with the llamacpp team to unlock the next generation of local AI so he…

Clem Delangue posted about someone flying to work with the llama.cpp team on developing next-generation local AI capabilities, framed as meta commentary on headlines related to the endeavor. The post

local-aiclem-delangue--x

Long-Horizon Manipulation via Trace-Conditioned VLA Planning

arXiv:2604.21924v1 Announce Type: new Abstract: Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to c

researcharxiv-cs-ro

Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMs

arXiv:2507.03933v3 Announce Type: replace Abstract: Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist hum

Low Cost, High Efficiency: LiDAR Place Recognition in Vineyards with Matryoshka Representation Learning

arXiv:2601.18714v2 Announce Type: replace-cross Abstract: Localization in agricultural environments is challenging due to their unstructured nature and lack of distinctive landmarks. Although agricult

Low-Rank Adaptation Redux for Large Models

model-releasesarxiv-cs-lg

arXiv:2604.21905v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation

LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imaging

arXiv:2511.18513v2 Announce Type: replace Abstract: Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruc

researcharxiv-cs-cv

M-CARE: Standardized Clinical Case Reporting for AI Model Behavioral Disorders, with a 20-Case Atlas and Experimental Validation

arXiv:2604.20871v1 Announce Type: cross Abstract: We introduce M-CARE (Model Clinical Assessment and Reporting for Evaluation), a clinical case report framework for AI model behavioral disorders adapt

Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions

arXiv:2604.21871v1 Announce Type: new Abstract: Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decisio

safetyarxiv-cs-cl

Machine learning and digital pragmatics: Which word category influences emoji use most?

arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1

Maine's governor vetoes a bill that would have led to US' first state pause on data centers, citing its failure to exempt a project in a distressed mill town (Jenna Russell/New York Times)

Jenna Russell / New York Times: Maine's governor vetoes a bill that would have led to US' first state pause on data centers, citing its failure to exempt a project in a distressed mill town — Gov. Jan

industrytechmeme

Applications

Mapping the Political Discourse in the Brazilian Chamber of Deputies: A Multi-Faceted Computational Approach

arXiv:2604.21897v1 Announce Type: new Abstract: Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper,

applicationsarxiv-cs-cl

MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations

model-releasesarxiv-cs-cv

arXiv:2602.18792v3 Announce Type: replace Abstract: Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interp

Materialistic RIR: Material Conditioned Realistic RIR Generation

arXiv:2604.21119v1 Announce Type: cross Abstract: Rings like gold, thuds like wood! The sound we hear in a scene is shaped not only by the spatial layout of the environment but also by the materials o

MathDuels: Evaluating LLMs as Problem Posers and Solvers

model-releasesarxiv-cs-cl

arXiv:2604.21916v1 Announce Type: new Abstract: As frontier language models attain near-ceiling performance on static mathematical benchmarks, existing evaluations are increasingly unable to different

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations

arXiv:2604.20848v1 Announce Type: cross Abstract: Large Language Model (LLM)-based recommendation systems have demonstrated remarkable capabilities in understanding user preferences and generating per

MCAP: Deployment-Time Layer Profiling for Memory-Constrained LLM Inference

model-releasesarxiv-cs-lg

arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili

mcdok at SemEval-2026 Task 13: Finetuning LLMs for Detection of Machine-Generated Code

arXiv:2604.21365v1 Announce Type: cross Abstract: Multi-domain detection of the machine-generated code snippets in various programming languages is a challenging task. SemEval-2026 Task~13 copes with

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding

arXiv:2604.21268v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogen

local-aiarxiv-cs-ai

Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review

arXiv:2603.18740v2 Announce Type: replace-cross Abstract: Automated Code Review (ACR) systems integrating Large Language Models (LLMs) are increasingly adopted in software development workflows, rangi

Measuring Opinion Bias and Sycophancy via LLM-based Coercion

model-releasesarxiv-cs-cl

arXiv:2604.21564v1 Announce Type: new Abstract: Large language models increasingly shape the information people consume: they are embedded in search, consulted for professional advice, deployed as age

Meet the 19-meter Cretaceous kraken that swam with mosasaurs

Fossilized jaws reveal that enormous octopuses growing up to 19 meters long were top predators in the oceans during the Cretaceous Period, potentially making them the largest marine animals and invert

industryars-technica

Meta and Amazon reach a multibillion-dollar, multiyear deal for Meta to rent hundreds of thousands of Amazon's Graviton chips for its AI inference needs (Matt Day/Bloomberg)

Matt Day / Bloomberg: Meta and Amazon reach a multibillion-dollar, multiyear deal for Meta to rent hundreds of thousands of Amazon's Graviton chips for its AI inference needs — Amazon.com Inc. and Met

industrytechmeme

Meta inks deal to use more Amazon chips (Ina Fried/Axios)

Ina Fried / Axios: Meta inks deal to use more Amazon chips — Meta on Friday announced a deal to use Amazon-designed chips to help deliver its next generation of AI models. … - The new pact, which buil

industrytechmeme

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling

arXiv:2507.01829v2 Announce Type: replace-cross Abstract: Multi-timescale sequence modeling relies on capturing both local fast dynamics and global slow context; yet, maintaining these capabilities un

Micro-DualNet: Dual-Path Spatio-Temporal Network for Micro-Action Recognition

arXiv:2604.21011v1 Announce Type: new Abstract: Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential fo

researcharxiv-cs-cv

MiMIC: Mitigating Visual Modality Collapse in Universal Multimodal Retrieval While Avoiding Semantic Misalignment

arXiv:2604.21326v1 Announce Type: cross Abstract: Universal Multimodal Retrieval (UMR) aims to map different modalities (e.g., visual and textual) into a shared embedding space for multi-modal retriev

Mind the Gap: Optimal and Equitable Encouragement Policies

arXiv:2309.07176v5 Announce Type: replace Abstract: In consequential domains, it is often impossible to compel individuals to take treatment, so that optimal policy rules are merely suggestions in the

local-aiarxiv-cs-lg

Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs

arXiv:2604.21092v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into complex software systems enables the generation of human-understandable explanations of opaque AI processe

Misinformation Span Detection in Videos via Audio Transcripts

arXiv:2604.21767v1 Announce Type: new Abstract: Online misinformation is one of the most challenging issues lately, yielding severe consequences, including political polarization, attacks on democracy

MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting

arXiv:2604.21489v1 Announce Type: cross Abstract: Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency d

Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards

arXiv:2510.18731v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate strong capabilities in single-turn instruction following but suffer from Lost-in-Conversation (LiC), a degra