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Measuring 3D Spatial Geometric Consistency in Dynamic Video Generation

arXiv:2603.19048v2 Announce Type: replace Abstract: Recent generative models can produce high-fidelity videos, yet they often exhibit 3D spatial geometric inconsistencies. Existing evaluation methods

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Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation

DGX agent

arXiv:2602.14469v3 Announce Type: replace Abstract: Reverse Chain-of-Thought Generation (RCG) synthesizes reasoning traces from query-answer pairs, but it risks producing post-hoc rationalizations: wh

researcharxiv-cs-cl

7 Jul 2026

Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents

arXiv:2607.04528v1 Announce Type: new Abstract: Software-agent benchmarks usually report whether an agent solves a task, but the agent reaches that outcome through a harness that controls what it sees

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

applicationsarxiv-cs-ai

Measuring What Matters: A Unified Evaluation Framework for GNN Explainability

arXiv:2607.04600v1 Announce Type: new Abstract: Graph eXplainable AI (G-XAI) is increasingly important for making Graph Neural Networks interpretable and accountable. While a growing number of explain

Mechanism-level routing failure in LLMs over Lean-verified algebraic structures

model-releasesarxiv-cs-cl

arXiv:2607.04534v1 Announce Type: new Abstract: We present an empirical study of structural routing failure in large language models (LLMs) over a formally verified algebraic corpus. The task requires

Agents

MechMath Agent Team: LLM Driven Agents for Mathematical Research

arXiv:2607.04394v1 Announce Type: new Abstract: AI reasoning has become a central focus in contemporary artificial intelligence, largely driven by the success of large language models. However, mathem

agentsarxiv-cs-ai

MedCalc-Pro: Solving Complex Medical Calculations with LLM Agents

arXiv:2607.02879v1 Announce Type: new Abstract: Current benchmarks for evaluating large language models (LLMs) in medical calculation are largely based on simplified settings, where each patient case

Medi-Gemma: A Hybrid Clinical Decision Support System Integrating Deterministic EMR Analytics and Retrieval-Augmented Generation

arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over

Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules

arXiv:2606.16337v3 Announce Type: replace Abstract: Predictive modeling for clinical decision support requires not only strong predictive performance but also transparent decision logic. Although deep

researcharxiv-cs-ai

MedMambaLite: Hardware-Aware Mamba for Medical Image Classification

arXiv:2508.05049v1 Announce Type: cross Abstract: AI-powered medical devices have driven the need for real-time, on-device inference such as biomedical image classification. Deployment of deep learnin

local-aiarxiv-cs-cv

MeGA-MP: Metric Graph Advection Message Passing -- A Physics-Informed Message Passing Operator for Advection-Dominated Metric Graphs

arXiv:2607.05167v1 Announce Type: new Abstract: Many real-world systems are organized as networks where spatio-temporal dynamics unfold along connections and not discretely between nodes. Examples inc

safetyarxiv-cs-lg

Memory chipmaker SK hynix seeks to raise $28B through US IPO

model-releasessiliconangle

SK hynix Inc., the South Korean firm that rivals Samsung Electronics Co. Ltd. and Micron Technology Inc. as one of the world’s top memory chipmakers, said today it will sell almost 17.8 million shares

Memory-Efficient FastText: A Comprehensive Approach Using Double-Array Trie Structures and Mark-Compact Memory Management

model-releasesarxiv-cs-cl

arXiv:2506.01254v2 Announce Type: replace Abstract: FastText remains a practical choice for industrial word representation because it can synthesize vectors for out-of-vocabulary words from character

Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture

arXiv:2607.04391v1 Announce Type: new Abstract: Long-term memory remains a structural weakness of AI agents. The dominant approach, retrieval-augmented generation (RAG), relies on embedding-based simi

local-aiarxiv-cs-cl

MemPose: Category-level Object Pose Estimation with Memory

arXiv:2607.04930v1 Announce Type: cross Abstract: In the pursuit of robust and generalizable category-level object pose estimation, most existing methods adopt parametric formulations that learn effec

Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets

arXiv:2607.03540v1 Announce Type: new Abstract: Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detec

researcharxiv-cs-cl

MentalThink: Shaping Thoughts in Mental SVG World

arXiv:2607.03530v1 Announce Type: new Abstract: We introduce MentalThink, a visual-symbolic reasoning paradigm that equips Multimodal LLMs (MLLMs) with an executable mechanism for 'mental' visualizati

safetyarxiv-cs-ai

MergeSurv: Merging-Based Continual Learning for Survival Analysis on Whole-Slide Images

arXiv:2607.04747v1 Announce Type: new Abstract: Survival analysis on Whole Slide Images (WSIs) is important in computational pathology for prognosis estimation and treatment planning. However, existin

Meta announces that it will be updating its glasses with a new feature that disables the camera if someone tampers with the glasses' privacy LED light (Victoria Song/The Verge)

Victoria Song / The Verge: Meta announces that it will be updating its glasses with a new feature that disables the camera if someone tampers with the glasses' privacy LED light — The company is rolli

industrytechmeme

Meta says Muse Image includes an invisible watermarking system called Content Seal and previews a web tool to check whether an image was generated with Meta AI (Karissa Bell/Engadget)

Karissa Bell / Engadget: Meta says Muse Image includes an invisible watermarking system called Content Seal and previews a web tool to check whether an image was generated with Meta AI — It has rate l

industrytechmeme

MetaCaDI: A Meta-Learning Framework for Causal Discovery from Multiple Environments with Unknown Interventions

arXiv:2510.22298v2 Announce Type: replace-cross Abstract: Uncovering the causal mechanisms of complex real-world systems remains a significant challenge, as these systems often entail high data collec

applicationsarxiv-cs-lg

Metallic Ultrasound Waveguides as a Distributed Tactile Sensing Platform for Contact Localization, Force Estimation, and Material Class Discrimination

model-releasesarxiv-cs-ro

arXiv:2607.02827v1 Announce Type: new Abstract: Tactile sensing is central to how robotic systems interact with the real world, yet current solutions face a tradeoff between sensing area and system co

MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration

arXiv:2211.10872v2 Announce Type: replace Abstract: Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability t

Meta’s new Muse Image model can pull other Instagram users into AI photos

Meta is launching the first AI image generation model made by its Superintelligence Labs division. The Muse Image model now powers the image-making tools across the Meta AI app, Instagram, and WhatsAp

industrythe-verge-ai

// MetaSkill-Evolve // Great paper on self-improving agents. Most self-improving agents rewrite what the agent does and leave how it improve…

// MetaSkill-Evolve // Great paper on self-improving agents. Most self-improving agents rewrite what the agent does and leave how it improves frozen and hand-authored. That improvement procedure never

model-releasesdair-ai--x

MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution

arXiv:2607.05297v1 Announce Type: new Abstract: Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further

local-aiarxiv-cs-ai

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du

applicationsarxiv-cs-ai

Metronome: Bound the Cache, Keep the Beat for Real-Time Interaction Model Serving

arXiv:2607.02640v1 Announce Type: cross Abstract: Real-time interaction models -- Moshi, MiniCPM-o, Qwen-Omni -- turn serving into a periodic real-time task: on every frame a session ingests streaming

MGCA-Net: Multi-Grained Category-Aware Network for Open-Vocabulary Temporal Action Localization

arXiv:2511.13039v2 Announce Type: replace Abstract: Open-Vocabulary Temporal Action Localization (OV-TAL) aims to recognize and localize instances of any desired action categories in videos without ex

Michigan sees explosive outbreak of diarrheal parasite with over 700 cases

Michigan experienced a rapid cyclosporiasis outbreak, with nearly 700 confirmed cases quadrupling from roughly 170 in less than a week . The leading theory links the infection to contaminated fresh pr

industryars-technica

Microsoft is reportedly ditching OpenAI’s and Anthropic’s AI models in favor of its own to cut costs

Microsoft Corp. is reportedly transitioning away from using OpenAI Group PBC’s and Anthropic PBC’s most advanced artificial intelligence models in favor of its own — increasingly leaning on the new Mi

industrysiliconangle

miMamba: EEG-based Emotion Recognition with Multi-scale Inverted Mamba Models

arXiv:2409.07589v2 Announce Type: cross Abstract: EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative

Minimum Block Width for Universal Approximation by Residual Neural Networks with Inner Width One

arXiv:2607.04597v1 Announce Type: new Abstract: In this paper, we study the universal approximation property of residual neural networks, and obtain some new results. For input and output dimensions d

MIRAGE: Defending Long-Form RAG Against Misinformation Pollution

arXiv:2607.05069v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves factuality by grounding LLMs in external evidence, but real-world retrieval is often polluted: semanticall

applicationsarxiv-cs-cl

Missing Data Imputation under Manifold Hypothesis

arXiv:2607.03641v1 Announce Type: cross Abstract: The manifold hypothesis posits that high-dimensional data are concentrated near a low-dimensional embedded manifold. Recent advances in mixture variat

local-aiarxiv-cs-lg

Missingness as Signal: Channel-Independent Spectrogram Learning for Clinical Time Series Prediction

arXiv:2607.02938v1 Announce Type: new Abstract: Clinical time series prediction in intensive care units remains challenging due to heterogeneous physiological variables and informative missingness. Th

Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models

arXiv:2409.16663v5 Announce Type: replace-cross Abstract: We propose the use of latent space generative world models to address the covariate shift problem in autonomous driving. A world model is a ne

safetyarxiv-cs-cv

Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models

arXiv:2607.03517v1 Announce Type: cross Abstract: Brownian Bridge Diffusion Models (BBDM) offer an appealing framework for image restoration and inverse problems by constructing a stochastic bridge fr

safetyarxiv-cs-cv

Hardware

MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems

arXiv:2607.02558v1 Announce Type: cross Abstract: As machine learning shifts from laboratory curiosity to critical infrastructure, the systems that sustain it span an extraordinary range, from sub-mil

hardwarearxiv-cs-lg

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training

model-releasesarxiv-cs-cv

arXiv:2602.06285v2 Announce Type: replace Abstract: Recent research in geospatial machine learning has demonstrated that models pretrained with self-supervised learning on Earth observation data can p

Model Confidence-Guided Multi-Image Fusion of Fundus Images for Diabetic Retinopathy Diagnosis

arXiv:2607.03643v1 Announce Type: cross Abstract: Purpose: Early screening for eye diseases is critical in low- and middle-income countries where access to care is limited. We investigate whether a co

Model Predictive Path Integral PID Control for Learning-Based Path Following

arXiv:2603.29499v2 Announce Type: replace-cross Abstract: Classical proportional--integral--derivative (PID) control remains widely used in industrial control systems, while model predictive control (

Modeling the Impact of Visual Brand Language on Attention, Object Recognition, and Memory Retrieval

arXiv:2607.02929v1 Announce Type: cross Abstract: Visual brand language is the set of visual properties that convey brand identity for a product. What is the impact of visual brand language on a perso

researcharxiv-cs-ai

Modular Foundation Models for Time-Series Perception in Digital Twins

model-releasesarxiv-cs-lg

arXiv:2607.03585v1 Announce Type: new Abstract: Engineering Digital Twins and Prognostics and Health Management (PHM) systems rely on robust perception modules to extract actionable information from h

Monitoring discriminative ML models using Amazon SageMaker AI with MLflow

Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use case. This post shows how you can use ope

industryaws-ml-blog

Moonstone: A Multimodal Foundation Model and Benchmark for Lunar Remote Sensing

arXiv:2607.03644v1 Announce Type: cross Abstract: Decades of orbital missions have produced multi-modal remote sensing data for the Moon, spanning optical imagery, spectroscopy, thermal emission, rada

MoP-JEPA: Hard-Assigned Predictor Mixtures for Stochastic JEPA World Models

arXiv:2607.05238v1 Announce Type: new Abstract: JEPA world models predict the next latent state with a single deterministic predictor trained by latent regression. We show that this fails structurally

researcharxiv-cs-ai