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arXiv:2610.16252v1 Announce Type: new Abstract: Whole-body human-object interaction (HOI) generation requires coordinating body and finger motion, object trajectories, and time-varying contacts. Exist

local-aiarxiv-cs-cv

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MFVSR: A Multi-Style and Fine-Grained Benchmark for Video Subtitle Removal

DGX agent

arXiv:2610.18461v1 Announce Type: new Abstract: Video subtitle removal (VSR) is an important video restoration task, yet existing evaluation remains limited by low-resolution datasets, fragmented test

model-releasesarxiv-cs-cv

14 Oct 2026

MHVF: Training-Free GUI Grounding via Verification-Guided Multi-Hypothesis Search

model-releasesarxiv-cs-cv

arXiv:2610.17792v1 Announce Type: new Abstract: GUI grounding enables web agents to translate natural-language instructions into actionable interface locations. However, dense layouts and small, visua

MicroCLIP: Connecting Text and Microscopy Images via Contrastive Language--Image Pretraining

arXiv:2610.17866v1 Announce Type: new Abstract: Understanding fluorescence microscopy images is fundamental to automating biological research. However, existing methods typically learn predefined conc

safetyarxiv-cs-cv

Industry

Microsoft has a new machine learning tool to improve weather forecasts

Old-school physics-based weather forecasting and even new AI models typically become less reliable beyond two weeks, a problem Microsoft claims to have solved using machine learning. Researchers with

industrythe-verge-ai

Local Ai

microsoft/UserRepGen-4B

https://preview.redd.it/gwb4of5vmivh1.png?width=2400&format=png&auto=webp&s=853f4cf25b4140ccf8b151b4124547788a544b33 UserRepGen-4B is a fine-tuned Qwen3.5-4B language model that generates a structured

local-air-localllama

MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation

arXiv:2610.17354v1 Announce Type: new Abstract: Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which

researcharxiv-cs-cv

MiMaAlign: Hierarchical Micro-Macro Alignment for Physically Plausible Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.16482v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made remarkable progress in generating high-fidelity visuals, yet their outputs still often exhibit physically

Minimax Optimality of Shampoo for Nonstationary Stochastic Optimization

arXiv:2610.16923v1 Announce Type: cross Abstract: We develop a comprehensive theoretical analysis of Matrix Shampoo for tracking time-varying optima in nonstationary stochastic optimization. We derive

Minimax Rates and Improved Spectral Convergence for Multi-Manifold Clustering

arXiv:2610.15892v1 Announce Type: cross Abstract: We study eigenpair estimation for the tensorized, density-weighted Laplace--Beltrami operator from n independent data points sampled from a multi-mani

Minimax rates for pointwise CATE estimation: the role of design smoothness

arXiv:2610.18623v1 Announce Type: cross Abstract: We study the role of design smoothness in the minimax estimation of conditional average treatment effects at a fixed covariate point. For design densi

Minimum Volume Optimal Transport for Multivariate Conformal Prediction

arXiv:2610.14907v1 Announce Type: cross Abstract: Optimal transport (OT) enables multivariate conformal prediction (CP) to construct flexible prediction sets that reflect the underlying complex distri

Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree

arXiv:2610.16906v1 Announce Type: new Abstract: Multi-modal fusion for 3D object detection assumes that cameras and LiDAR are broadly complementary. In practice, how much each modality is trusted at a

safetyarxiv-cs-cv

MIRRA: Fast, High-Fidelity Molecular Generation with Chemistry-Informed Discrete Flow Matching

arXiv:2610.17244v1 Announce Type: new Abstract: Fast, high-fidelity molecular generation requires accurate chemical choices and efficient sampling. Chemical building blocks reduce graph size, but make

MIRROR: Reflecting Hidden Symmetries from Offline Robot Interaction Data

arXiv:2610.17422v1 Announce Type: new Abstract: Symmetry-aware robot policy learning requires coupled observation-action transformations. For pixel observations, even simple physical symmetries can in

safetyarxiv-cs-ro

MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series

arXiv:2610.17715v1 Announce Type: new Abstract: Flow matching has emerged as a powerful alternative to diffusion models for generative modeling, but standard conditional flow matching is fundamentally

Local Ai

MIST: Multi-Scale Spatial Context for Gene Expression Prediction from Histology

arXiv:2610.18769v1 Announce Type: new Abstract: Predicting spatial gene expression from standard H&E images could extend molecular analysis to tissues without spatial transcriptomic measurements. A st

local-aiarxiv-cs-cv

Mitigating Black-Box Score-Based Query Attacks via Gradient Confusion

arXiv:2610.17382v1 Announce Type: new Abstract: Score-based black-box adversarial attacks pose a serious threat to deployed machine learning systems by exploiting repeated model queries to craft adver

Mixed Precision Scaling Laws for Quantized Pretraining

arXiv:2610.17637v1 Announce Type: new Abstract: Since scaling laws were introduced for modern LLMs (Kaplan et al., 2020), several works have extended them to account for quantization, tracking the eme

Mixing Regularization for Average-Reward Q-Learning and Q-Planning

arXiv:2610.14988v1 Announce Type: new Abstract: The average-reward setting for reinforcement learning is challenging because its Bellman operator is known to contract in span only when the underlying

Mixture of GFlowNets

arXiv:2610.17007v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) learn a policy that samples compositional objects in proportion to an unnormalized reward R(x). This makes them use

Applications

ML-CLAPPS: A Probabilistic Framework for Imbalanced Multilabel Learning under Class Prioritization

arXiv:2610.15816v1 Announce Type: cross Abstract: Real-world datasets often exhibit severe class imbalance, degrading the performance of deep learning models, particularly on rare classes. While imbal

applicationsarxiv-cs-cv

ML Engineering Agents - A Data Management Perspective

arXiv:2610.16919v1 Announce Type: cross Abstract: Machine learning engineering (MLE) agents are emerging as a new paradigm for automating end-to-end ML pipeline development. Using large language model

MLAfication: Efficiently Enabling High-Fidelity MLA for Modern LLMs

arXiv:2610.17202v1 Announce Type: new Abstract: Multi-Head Latent Attention (MLA) compresses the KV cache into a latent representation, reducing inference memory and bandwidth. Existing MHA2MLA/TransM

Applications

MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs

arXiv:2508.21044v2 Announce Type: replace Abstract: Video Large Language Models (VLLMs) excel in video understanding, but their excessive visual tokens pose a significant computational challenge for r

applicationsarxiv-cs-cv

MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision

arXiv:2610.17856v1 Announce Type: new Abstract: Time-series analysis is increasingly studied in multimodal settings, yet most benchmarks pair temporal signals with text or with visualizations derived

Mobility-Budget-Constrained Submodular Maximization for Distributed Semantic Multi-Robot Exploration

arXiv:2610.17562v1 Announce Type: new Abstract: Multi-robot exploration under communication and mobility constraints requires balancing information gain with reachability. We present a distributed sem

researcharxiv-cs-ro

Mobility Helps Learning: Unsupervised Model Adaptation for Object Recognition via Movement

arXiv:2610.15846v1 Announce Type: new Abstract: Movable agents, such as autonomous vehicles and robots, should be able to autonomously adapt their pre-trained object recognition models to new environm

safetyarxiv-cs-cv

Mode Collapse of Mean-Field Variational Inference

arXiv:2510.17063v2 Announce Type: replace-cross Abstract: Mean-field variational inference (MFVI) is a widely used method for approximating high-dimensional probability distributions by product measur

Model-Based Online Decision Making via Generative Trajectory Planning

arXiv:2610.18677v1 Announce Type: new Abstract: Online decision-making faces a tension between efficient inference and long-horizon reasoning. Value-based methods rely on short-horizon bootstrapping t

Agents

Model-Based Trailer-Sway Suppression for Autonomous Passenger Vehicles

arXiv:2610.15747v1 Announce Type: new Abstract: Trailer sway is a persistent contributor to severe crashes among light passenger vehicles towing trailers, yet it remains largely unaddressed by the aut

agentsarxiv-cs-ro

Modeling and Control of a Rigid-soft Hybrid-link Humanoid Robot

arXiv:2610.15073v1 Announce Type: new Abstract: Physical flexibility plays a significant role not only in human motions but also in robot motions. For example, a humanoid robot with passive and flexib

researcharxiv-cs-ro

ModRes: A modification of the ResPlan dataset ready for floor plan analysis and graph machine learning

arXiv:2610.17178v1 Announce Type: new Abstract: Floor plan datasets underpin computational analysis of building layouts, spatial connectivity and graph machine learning. However, publicly available da

Moment-Based Anomaly Detection in High-Dimensional Mixed Data

arXiv:2610.16285v1 Announce Type: cross Abstract: We propose an anomaly detection method for high-dimensional mixed-type data that maps heterogeneous features to a common scale via standardized moment

Monarch-Muon: Structure-Aware Muon for Fast and Memory-Efficient Pretraining

arXiv:2610.17429v1 Announce Type: new Abstract: Training large language models is constrained by both wall-clock time and memory footprint, and recent matrix-aware optimizers sharpen this tradeoff: Mu

Monitoring for Shifts at Unknown Times: Parameter-Free Conditional Conformal Martingales

arXiv:2610.17343v1 Announce Type: cross Abstract: Conditional conformal test martingales provide sequential tests for detecting distribution shifts, using a fixed reference dataset to avoid contaminat

More Domains, No Gains? FLO: Fast-Slow Reciprocal Learning for Multi-Domain Graph Pre-training

arXiv:2610.14748v1 Announce Type: new Abstract: Inspired by the great success of foundation models in the development of artificial general intelligence, Graph Foundation Models (GFMs) have recently a

Tutorials

MORE: Learning Motion-Oriented Registers for Driving World Models and Planning

arXiv:2610.14871v1 Announce Type: new Abstract: By predicting future states, latent world models provide rich self-supervision for end-to-end driving, but often inherit dense features from pretrained

tutorialsarxiv-cs-cv

Morphology-aware deep learning predicts colorectal cancer survival from whole-slide images

arXiv:2610.17603v1 Announce Type: new Abstract: Background: Five-year survival prediction from hematoxylin-and-eosin whole-slide images could support risk stratification, but the task is weakly superv

researcharxiv-cs-cv

Tutorials

MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning

arXiv:2610.15205v1 Announce Type: cross Abstract: Efficient task scheduling in heterogeneous computing systems remains a fundamental challenge in embedded and high-level synthesis flows. This paper pr

tutorialsarxiv-cs-lg

MOSAIC: Mode- and Support-Aware Inference-Time Control of Robot Diffusion Models

arXiv:2610.17001v1 Announce Type: new Abstract: Generative policies such as diffusion models provide expressive data-driven priors for robot behavior, yet the situations a robot faces at execution tim

safetyarxiv-cs-ro

Moving a running model's layers between GPUs mid-reply (8 ms, no re-prefill)

model-releasesr-localllama

I've been working on an inference engine called jitllm. The idea came from my background in operating systems and JIT compilers: generate kernels for whatever hardware is there, and treat layers a bit

MP-MNCA: Morphology-Prior Masked Neighbor Cross-Attention for Efficient Spatial Domain Identification

arXiv:2610.16212v1 Announce Type: new Abstract: Spatial transcriptomics jointly captures molecular state, tissue morphology, and spatial organization, yet spatial-domain methods are typically compared

researcharxiv-cs-cv

MRFlow: Mechanism-Structured Residual Flow Matching for Virtual Cell Perturbation Prediction

arXiv:2610.13966v1 Announce Type: new Abstract: Predicting cellular responses to chemical and genetic perturbations is a central test for AI virtual cells, yet many single-cell models reduce each cond

MSC: Multi-Stage Caster-aware Control Framework with Uncertainty-Aware NMPC and RL-based Execution Layer

arXiv:2610.16199v1 Announce Type: cross Abstract: Freely swiveling casters are widely adopted in industrial AMRs/SDVs for their mechanical simplicity and load capacity. However, caster misalignment du

Agents

Multi-Agent Deferred-Decision Trajectory Optimization with Anytime-Valid Target Retention for Moving Candidates

arXiv:2610.17003v1 Announce Type: cross Abstract: We study multi-agent terminal interception when one of several moving candidates is the unknown target and both target identity and candidate terminal

agentsarxiv-cs-lg

Agents

Multi-modal Representation Fusion for Long-term Microsurgical Anastomosis Trajectory Anticipation

arXiv:2610.14492v1 Announce Type: cross Abstract: Microsurgical anastomosis is one of the most challenging and sophisticated procedures for surgical robotics, requiring accurate manipulation of surgic

agentsarxiv-cs-cv

Tutorials

Multi-Stream Residual Computation in Diffusion Language Models

arXiv:2610.18407v1 Announce Type: new Abstract: Diffusion language models reconstruct masked tokens in parallel, offering an alternative to autoregressive generation. Yet their Transformer backbones t

tutorialsarxiv-cs-lg