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MIRAGE: A Micro-Interaction Relational Architecture for Grounded Exploration in Multi-Figure Artworks

arXiv:2604.23788v1 Announce Type: new Abstract: Appreciating multi-figure paintings requires understanding how characters relate through subtle cues like gaze alignment, gesture, and spatial arrangeme

safetyarxiv-cs-cv

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Research

MirrorMark: A Distortion-Free Multi-Bit Watermark for Large Language Models

DGX agent

arXiv:2601.22246v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become integral to applications such as question answering and content creation, reliable content attribution

researcharxiv-cs-ai

28 Apr 2026

Mitchell Hashimoto, co-founder of HashiCorp, says his terminal application Ghostty will move off GitHub, citing GitHub's frequent outages (Mitchell Hashimoto)

Mitchell Hashimoto: Mitchell Hashimoto, co-founder of HashiCorp, says his terminal application Ghostty will move off GitHub, citing GitHub's frequent outages — I'm GitHub user 1299, joined Feb 2008. —

industrytechmeme

Tutorials

Mitigating Error Amplification in Fast Adversarial Training

arXiv:2604.24332v1 Announce Type: new Abstract: Fast Adversarial Training (FAT) has proven effective in enhancing model robustness by encouraging networks to learn perturbation-invariant representatio

tutorialsarxiv-cs-lg

Mixture of Heterogeneous Grouped Experts for Language Modeling

arXiv:2604.23108v1 Announce Type: cross Abstract: Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficient

mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA

arXiv:2508.05318v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for expanding the knowledge capacity of Multimodal Large Language Mo

ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs

arXiv:2604.23053v1 Announce Type: new Abstract: Mixed Binary Quadratic Programs (MBQPs) are an important and complex set of problems in combinatorial optimization. As solving large-scale combinatorial

applicationsarxiv-cs-lg

MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation

model-releasesarxiv-cs-lg

arXiv:2506.01897v5 Announce Type: replace Abstract: With increasing size of large language models (LLMs), full-parameter fine-tuning imposes substantial memory demands. To alleviate this, we propose a

Mobile-R1: Towards Interactive Capability for VLM-Based Mobile Agent via Systematic Training

arXiv:2506.20332v4 Announce Type: replace Abstract: Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinfor

MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback

arXiv:2604.23107v1 Announce Type: cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding. Classical estimators such as inverse probability weighti

applicationsarxiv-cs-lg

Model-Free Inference of Investor Preferences: A Relative Entropy IRL Approach

arXiv:2604.24280v1 Announce Type: new Abstract: We present a framework using Relative Entropy Inverse Reinforcement Learning (RE-IRL) to recover investor reward functions from observed investment acti

safetyarxiv-cs-lg

Local Ai

Model page: https://ollama.com/library/laguna-xs.2

Laguna XS 2 is a compact language model available through Ollama's model library, designed for efficient inference on resource-constrained devices. The model represents an update or variant in the Lag

local-aiollama--x

Local Ai

Model page: https://ollama.com/library/nemotron3

Nemotron-3 is an open-source language model available through Ollama's model library, likely representing NVIDIA's Nemotron-3 family of instruction-tuned models designed for various NLP tasks. The mod

local-aiollama--x

Modeling Behavioral Intensity and Transitions for Generative Recommendation

arXiv:2604.24472v1 Announce Type: cross Abstract: Multi-behavior recommendation aims to predict user conversions by modeling various interaction types that carry distinct intent signals. Recently, gen

Modeling Induced Pleasure through Cognitive Appraisal Prediction via Multimodal Fusion

arXiv:2604.23753v1 Announce Type: new Abstract: Multimodal affective computing analyzes user-generated social media content to predict emotional states. However, a critical gap remains in understandin

Modular Sensory Stream for Integrating Physical Feedback in Vision-Language-Action Models

arXiv:2604.23272v1 Announce Type: new Abstract: Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approache

applicationsarxiv-cs-ro

Monocular Depth Estimation via Neural Network with Learnable Algebraic Group and Ring Structures

arXiv:2604.24328v1 Announce Type: new Abstract: Monocular depth estimation (MDE) has witnessed remarkable progress driven by Convolutional Neural Networks and transformer-based architectures. However,

Tutorials

Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation

arXiv:2412.07160v3 Announce Type: replace Abstract: To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts

tutorialsarxiv-cs-cv

MotionHiFlow: Text-to-motion via hierarchical flow matching

arXiv:2604.23264v1 Announce Type: new Abstract: Text-to-motion generation aims to generate 3D human motions that are tightly aligned with the input text while remaining physically plausible and rich i

safetyarxiv-cs-cv

Move-Then-Operate: Behavioral Phasing for Human-Like Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2604.23620v1 Announce Type: new Abstract: We present Move-Then-Operate, a Vision language action framework that explicitly decouples robotic manipulation into two distinct behavioral phases: coa

MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings

arXiv:2604.23530v1 Announce Type: cross Abstract: Multi-turn, long-horizon tasks are increasingly common for large language models (LLMs), but solving them typically requires many sequential model inv

MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches

arXiv:2604.22881v1 Announce Type: cross Abstract: Generative recommendation (GR) offers superior modeling capabilities but suffers from prohibitive inference costs due to the repeated encoding of long

safetyarxiv-cs-ai

Multi-Dimensional Evaluation of Sustainable City Trips with LLM-as-a-Judge and Human-in-the-Loop

arXiv:2604.24158v1 Announce Type: new Abstract: Evaluating nuanced conversational travel recommendations is challenging when human annotations are costly and standard metrics ignore stakeholder-centri

Multi-Plane HyperX: A Low-Latency and Cost-Effective Network for Large-Scale AI and HPC Systems

arXiv:2604.23519v1 Announce Type: cross Abstract: Multi-plane architectures have become increasingly prevalent in the Fat-Tree networks of AI data centers. By leveraging multiple ports on a single net

researcharxiv-cs-lg

Multi-Robot Motions in Milliseconds: Vector-Accelerated Primitives for Sampling-Based Planning

arXiv:2604.23960v1 Announce Type: new Abstract: In this paper, we extend the recent Vector-Accelerated Motion Planning (VAMP) framework to multi-robot motion planning (MRMP). We develop two vector-acc

researcharxiv-cs-ro

Multi-Scale Contrastive Learning for Video Temporal Grounding

arXiv:2412.07157v3 Announce Type: replace Abstract: Temporal grounding, which localizes video moments related to a natural language query, is a core problem of vision-language learning and video under

Multi-scale Dynamic Wake Modeling of Floating Offshore Wind Turbines via Fourier Neural Operators and Physics-Informed Neural Networks

arXiv:2604.23937v1 Announce Type: cross Abstract: Multi-scale dynamic wake prediction is essential for the real-time control and performance optimization of floating offshore wind turbines (FOWTs). In

researcharxiv-cs-lg

Multi-view Graph Convolutional Network with Fully Leveraging Consistency via Granular-ball-based Topology Construction, Feature Enhancement and Interactive Fusion

arXiv:2603.26729v2 Announce Type: replace-cross Abstract: The effective utilization of consistency is crucial for multi-view learning. GCNs leverage node connections to propagate information across th

Multi-View Synergistic Learning with Vision-Language Adaption for Low-Resource Biomedical Image Classification

model-releasesarxiv-cs-cv

arXiv:2604.23977v1 Announce Type: new Abstract: Accurate biomedical image classification under low-resource conditions remains challenging due to limited annotations, subtle inter-class visual differe

MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning

arXiv:2604.24186v1 Announce Type: cross Abstract: Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While Large Language Models (LLMs) have shown strong capab

safetyarxiv-cs-ai

Multimodal QUD: Inquisitive Questions from Scientific Figures

arXiv:2604.23733v1 Announce Type: new Abstract: Asking inquisitive questions while reading, and looking for their answers, is an important part in human discourse comprehension, curiosity, and creativ

researcharxiv-cs-cl

Multimodal Remote Inference

arXiv:2508.07555v3 Announce Type: replace Abstract: We consider a remote inference system with multiple modalities, where a multimodal machine learning (ML) model performs real-time inference using fe

safetyarxiv-cs-lg

Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES

arXiv:2604.24370v1 Announce Type: new Abstract: The shift from stand-level to individual-tree-level forest assessments supports improved biodiversity mapping, particularly in boreal ecosystems where t

Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction

arXiv:2604.24187v1 Announce Type: new Abstract: Wide Field-of-View (WFoV) reconstruction enhances 3D ultrasound imaging by providing valuable anatomical context for segmentation models and visualizati

MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples

arXiv:2511.10047v2 Announce Type: replace Abstract: Zero-shot anomaly classification (AC) and segmentation (AS) methods aim to identify and outline defects without using any labeled samples. In this p

Muscle Coactivation in the Sky: Geometry and Pareto Optimality of Energy vs. Aerodynamic Promptness and Multirotors as Variable Stiffness Actuators

arXiv:2602.14222v2 Announce Type: replace Abstract: In robotics and biomechanics, trading metabolic cost for kinematic readiness is a well-established principle. This paper formalizes this concept for

researcharxiv-cs-ro

MUSIC: Learning Muscle-Driven Dexterous Hand Control

arXiv:2604.23886v1 Announce Type: cross Abstract: We present a data-driven approach for physics-based, muscle-driven dexterous control that enables musculoskeletal hands to perform precise piano playi

Musk and Altman go to court

The trial between Elon Musk and OpenAI is officially upon us. And it is going to be a mess. As the two sides fight over the early days of AI, who deserves credit and cash for what, and more, we're lik

industrythe-verge-ai

Musk v. Altman: Musk testifies he's suing OpenAI because 'it is not okay to steal a charity' and its pivot sets a concerning precedent for philanthropic efforts (Bloomberg)

Bloomberg: Musk v. Altman: Musk testifies he's suing OpenAI because “it is not okay to steal a charity” and its pivot sets a concerning precedent for philanthropic efforts — Elon Musk testified Tuesda

industrytechmeme

Musk v. Altman: the judge asks Elon Musk and Sam Altman to 'control your propensity to use social media to make things worse', as opening statements begin (Madlin Mekelburg/Bloomberg)

Madlin Mekelburg / Bloomberg: Musk v. Altman: the judge asks Elon Musk and Sam Altman to “control your propensity to use social media to make things worse”, as opening statements begin — The judge ove

industrytechmeme

MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2604.23789v1 Announce Type: new Abstract: While video foundation models excel at single-shot generation, real-world cinematic storytelling inherently relies on complex multi-shot sequencing. Fur

MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender

arXiv:2408.08686v4 Announce Type: replace-cross Abstract: Language Models (LMs) have been widely used in recommender systems to incorporate textual information of items into item IDs, leveraging their

applicationsarxiv-cs-ai

Agents

MY HERMES AGENT ATE ACID AND HIJACKED MY TOUCHDESIGNER INSTANCE. The new TouchDesigner skill in @NousResearch Hermes Agent is wild. It turns…

MY HERMES AGENT ATE ACID AND HIJACKED MY TOUCHDESIGNER INSTANCE. The new TouchDesigner skill in @NousResearch Hermes Agent is wild. It turns Hermes into a creative operator for abstract visuals, motio

agentsnous-research--x

Tools

my white whale is when CC sometimes looks like it hangs during big file writes, I think we found it 😭

A developer named Thariq identified a performance issue in a codebase (likely a code editor or similar tool abbreviated as 'CC') where the application appears to freeze or become unresponsive during l

toolsthariq--x

Tools

Native Deployment Checks are now available

Native Deployment Checks can now be run on every Vercel deployment, processing linting and typechecking in parallel with the build process. These built-in checks integrate with existing integrations (

toolsvercel-blog

Neanderthal brains measure up to ours—literally

Neanderthal and modern human brains from the same time period had similar sizes , though average Neanderthal brain volume was roughly 1410 cm³, higher than the mean value for humans today . However, w

industryars-technica

Nearly Optimal Subdata Selection

model-releasesarxiv-cs-lg

arXiv:2604.23930v1 Announce Type: cross Abstract: When, in terms of the number of data points, the size of a dataset exceeds available computing resources, or when labeling is expensive, an attractive

Necessary and sufficient conditions for universality of Kolmogorov-Arnold networks

arXiv:2604.23765v1 Announce Type: new Abstract: We analyze the universal approximation property of Kolmogorov-Arnold Networks (KANs) in terms of their edge functions. If these functions are all affine

researcharxiv-cs-lg