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M3TR: Temporal Retrieval Enhanced Multi-Modal Micro-video Popularity Prediction

arXiv:2411.15455v3 Announce Type: replace-cross Abstract: Accurately predicting the popularity of micro-videos is a critical but challenging task, characterized by volatile, `rollercoaster-like' engag

applicationsarxiv-cs-ai

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Magnitude-Direction Decoupling for Fast Video Generation with Flow Matching Models

DGX agent

arXiv:2608.17695v1 Announce Type: new Abstract: Flow matching models for video generation achieve impressive performance but suffer from high computational overhead due to iterative denoising. In fact

researcharxiv-cs-cv

19 Aug 2026

MAGPIE-Net: Predicting short-duration heavy-rainfall events in station neighborhoods from multitemporal FY-4A AGRI observations

arXiv:2608.17753v1 Announce Type: new Abstract: Short-duration heavy-rainfall warning determines whether 1 h rainfall will exceed a threshold within a target-station neighborhood over the next few hou

MagViT: Interpretable Multi-Magnification Transformers with Patient-Level Model Selection for Breast Histopathology

arXiv:2608.16959v1 Announce Type: cross Abstract: Breast cancer is one of the most common types of cancer among women around the world. Rapid detection and early treatment can hinder its progress to m

MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation

arXiv:2608.17635v1 Announce Type: new Abstract: Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to

ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation

arXiv:2406.01586v4 Announce Type: replace-cross Abstract: Diffusion models have been verified to be effective in generating complex distributions from natural images to motion trajectories. Recent dif

safetyarxiv-cs-ai

MANIGUARD: A Benchmark and Data Suite for Specification-Grounded Safety Evaluation and Improvement of Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.17386v1 Announce Type: new Abstract: Foundation-model policies for robotic manipulation are advancing rapidly on task success, but rigorous evaluation of whether they succeed safely is stil

Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence

arXiv:2608.16975v1 Announce Type: new Abstract: With the rapid advancement of large language models, brain-language decoding has achieved remarkable progress. However, it remains unclear whether decod

safetyarxiv-cs-cl

Mask What Matters: Saliency-Guided Video Self-Supervised Learning for Autonomous Driving

arXiv:2608.17178v1 Announce Type: new Abstract: Video self-supervised learning through masked spatiotemporal prediction has emerged as a promising paradigm for learning feature representations from un

safetyarxiv-cs-cv

Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data

arXiv:2608.17244v1 Announce Type: cross Abstract: This paper addresses the limitations of Gaussian distribution assumptions in statistical sparse learning, particularly in modeling correlated and hete

researcharxiv-cs-ai

MCTS-KBQA: Monte Carlo Tree Search with Information Gain Rewards for Knowledge Base Question Answering

arXiv:2502.13428v2 Announce Type: replace-cross Abstract: This work investigates how to improve large language model (LLM)-based reasoning for knowledge base question answering (KBQA) via Monte Carlo

tutorialsarxiv-cs-ai

Measuring Narrative Polarization in Online Discourse

arXiv:2601.07398v2 Announce Type: replace-cross Abstract: Polarization research has demonstrated how people cluster in homogeneous groups with opposing opinions. However, this effect emerges not only

researcharxiv-cs-cl

MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning

arXiv:2608.17722v1 Announce Type: cross Abstract: Vision-Language models (VLMs) achieve outstanding performance largely due to the amount of training data available on the internet. At the same time,

tutorialsarxiv-cs-lg

Agents

Memory Is Communication: The Frontier Between Remembering and Signaling

arXiv:2608.17053v1 Announce Type: new Abstract: A bounded agent may obtain information for a decision from its own past, from peers, or from both sources. Retaining task-relevant history can reduce la

agentsarxiv-cs-ai

Memory Tree Guided Key Frame Querying for Efficient 3D Question Answering

arXiv:2608.18009v1 Announce Type: new Abstract: Answering questions accurately and efficiently in embodied scenarios presents significant challenges due to limited computational and memory resources f

MITRE-SAGE: A Multi-Agent Cybersecurity Question-Answering Model

model-releasesarxiv-cs-lg

arXiv:2608.16921v2 Announce Type: cross Abstract: Effective cybersecurity operations require timely and accurate analysis of large-scale heterogeneous security information; however, analysts increasin

Local Ai

Mixture-of-Expert Blocks Contain Strong Hallucination Detection Signals

arXiv:2608.17687v1 Announce Type: new Abstract: Despite their widespread use, Large Language Models (LLMs) remain limited by a fundamental problem: the generation of plausible but false content, known

local-aiarxiv-cs-ai

MobileWorldSafety: Benchmarking GUI Agent Safety Against Environmental Injection Attacks in Android Apps

arXiv:2608.17659v1 Announce Type: cross Abstract: LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. Howeve

MoE-ViE: Mixture of Experts Vision Encoder for Efficient Image and Video Understanding

arXiv:2608.17402v1 Announce Type: new Abstract: Vision encoders are a critical component of vision-language models, and scaling their capacity effectively improves performance. However, dense scaling

MoFE: A Novel Mixture-of-Experts Framework with Fourier Neural Operators for Cryptocurrency Forecasting

arXiv:2608.17342v1 Announce Type: cross Abstract: Forecasting cryptocurrency prices remains a formidable challenge due to inherent non-stationarity, abrupt regime shifts, and multi-scale stochastic de

tutorialsarxiv-cs-ai

MoNe: Modular Neural Memory for Efficient Long Context Inference

arXiv:2608.17616v1 Announce Type: new Abstract: We present MoNe, a lightweight modular neural memory that attaches to any frozen pretrained Transformer to enable long-context inference without retrain

Monitoring Pasture Restoration from Satellite Image Time Series: Caveats and Opportunities

arXiv:2608.17704v1 Announce Type: new Abstract: Monitoring nature restoration at scale is an important but difficult ecological problem. Deep learning methods to analyze satellite image time series (S

safetyarxiv-cs-cv

Monotone Classification with Relative Approximations

arXiv:2506.10775v3 Announce Type: replace Abstract: In monotone classification, the input is a multi-set P of points in R^d, each associated with a hidden label from {-1, 1}. The goal is to identify a

MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale

arXiv:2506.01297v5 Announce Type: replace Abstract: Representation learning of geospatial locations remains a core challenge in achieving general geospatial intelligence, with increasingly diverging p

MoRAX: Mobility-based Representation Augmentation for Geospatial Foundation Models

arXiv:2608.17848v1 Announce Type: new Abstract: Geospatial Foundation Models (GFMs) are emerging as a powerful paradigm for learning semantically rich and geographically consistent visual and physical

Local Ai

MotoSafety: Edge-AI with Learned Temporal Importance for Two-Wheeler Collision Risk Assessment Under Time Pressure

arXiv:2608.17823v1 Announce Type: cross Abstract: Powered two-wheeler riders face critical safety challenges in low- and middle-income countries, yet limited studies exist on how cognitive stressors s

local-aiarxiv-cs-ai

MPC for underactuated spacecraft control with a Lyapunov supervised physics-informed neural network correction layer

arXiv:2606.13113v2 Announce Type: replace-cross Abstract: Underactuated spacecraft faces controllability limitations and heightened sensitivity to environmental disturbances, complicating attitude man

safetyarxiv-cs-ro

Mr.Dec: Daily-Scale Longitudinal Multimodal Modeling for 30-Day Readmission Prediction

arXiv:2608.16929v1 Announce Type: new Abstract: Predicting 30-day hospital readmission is essential for assessing patient stability and optimizing healthcare resources. As clinical risk evolves with t

applicationsarxiv-cs-lg

MS-MFAD : Multimodal large language models for Face Anti-spoofing Detection

model-releasesarxiv-cs-cv

arXiv:2608.17328v1 Announce Type: new Abstract: Facial biometric recognition systems currently face compound threats intertwining generative AI and high-fidelity physical spoofing. Existing defenses s

MSEditor: Toward Consistent Multi-Shot Video Editing

model-releasesarxiv-cs-cv

arXiv:2608.17559v1 Announce Type: new Abstract: In this paper, we tackle the problem of performing consistent, unified modifications to a multi-shot video sequence. This task is particularly challengi

Local Ai

Multi-Agent AI System for Radiology Report Structuring and Quality Assurance with Independent Radiologist Evaluation

arXiv:2608.18072v1 Announce Type: new Abstract: Purpose: To develop and evaluate a locally deployed multi-agent AI system for radiology report structuring and quality assurance. Materials and Methods:

local-aiarxiv-cs-cl

Multi-Observer Vehicle Localization Case Study with Roadside Radar and Connected Vehicle Sensing

arXiv:2608.16966v1 Announce Type: new Abstract: In modern intelligent transportation systems, it is essential to accurately estimate vehicle positions, especially in mixed traffic conditions where bot

applicationsarxiv-cs-cv

Hardware

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

arXiv:2506.18682v3 Announce Type: replace-cross Abstract: Recent advances in autonomous driving (AD) have highlighted the potential of hyperspectral imaging (HSI) for enhanced environmental perception

hardwarearxiv-cs-ai

Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges

arXiv:2608.17605v1 Announce Type: cross Abstract: Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction. In real conversations, users clarify goals, revise

safetyarxiv-cs-ai

MultiSigBERT: Beyond Survival Analysis through Multimodal and Sequential Modeling in Oncology

arXiv:2608.16972v1 Announce Type: new Abstract: Machine learning has become an essential component of modern healthcare, where the integration of heterogeneous data sources offers unprecedented opport

applicationsarxiv-cs-lg

N-gram-like Language Models Predict Naturalistic Reading Time Best

arXiv:2603.09872v2 Announce Type: replace Abstract: Recent work has found that contemporary language models such as transformers can become so good at next-word prediction that the probabilities they

researcharxiv-cs-cl

Network Denoising Revisited: A Ricci-Flow-Inspired Graph Diffusion Method

arXiv:2608.16923v1 Announce Type: cross Abstract: Networks provide a fundamental representation of relationships among entities. However, real-world networks are often corrupted by noise caused by mea

applicationsarxiv-cs-lg

Neural Operator-Based Nonlinear Nudging for Chaotic Dynamical Systems

model-releasesarxiv-cs-lg

arXiv:2508.05778v2 Announce Type: replace Abstract: Nudging is an empirical data assimilation technique that incorporates an observation-driven control term into the model dynamics. The trajectory of

Neuro-symbolic learning over OWL 2 DL via consequence-based compilation to differentiable circuits

arXiv:2608.17741v1 Announce Type: new Abstract: OWL 2 DL ontologies, grounded in the description logic SROIQ, express large knowledge bases in biomedicine and the Semantic Web. Neuro-symbolic (NeSy) l

researcharxiv-cs-ai

NeuroAbs: A Neuro-Symbolic RTL Abstraction Framework for Property Checking Acceleration

arXiv:2608.17304v1 Announce Type: cross Abstract: Formal verification is a crucial technique for ensuring the functional correctness of hardware designs. In the context of property checking, a key cha

tutorialsarxiv-cs-ai

NeuroPath: Brain-Inspired Dual-Pathway Graph Convolutional Networks for Skeleton-Based Action Recognition

arXiv:2608.17487v1 Announce Type: new Abstract: Skeleton-based action recognition aims to recognize human actions from sequences of human joint coordinates. Most existing Spatial-Temporal Graph Convol

NGS-Marker: Robust Native Watermarking for 3D Gaussian Splatting

arXiv:2608.17447v1 Announce Type: new Abstract: With the rapid development and adoption of 3D Gaussian Splatting (3DGS), the need for effective copyright protection has become increasingly critical. E

applicationsarxiv-cs-cv

No Gaussian Required: Contrastive Inverse Dynamics for JEPA World Models

arXiv:2608.17542v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting future embeddings, but the objective admits a trivial solution of a

safetyarxiv-cs-ai

Noisy group neurons with synchronous resetting for high-performance spiking neural networks

arXiv:2608.17394v1 Announce Type: new Abstract: Spiking neural networks (SNNs), characterized by bio-inspired neuronal dynamics and event-driven communication, have attained significant progress in re

Nonadaptive Learning in Robust Nonlinear Output Regulation

arXiv:2608.17262v1 Announce Type: cross Abstract: This paper considers robust nonadaptive regulation for general nonlinear systems in an output-feedback setting with arbitrarily high relative degree.

Nonlocal Transition Kernel for Efficient Learning of Restricted Boltzmann Machines

arXiv:2608.17450v1 Announce Type: cross Abstract: Learning restricted Boltzmann machines (RBMs) is computationally challenging because it requires expectations whose exact evaluation is generally intr

On detection probabilities of link invariants

arXiv:2509.05574v3 Announce Type: replace-cross Abstract: We prove that, for many standard link invariants, both the proportion of distinct invariant values and the detection probability among prime a

On Stability in Optimistic Bilevel Optimization

arXiv:2408.13323v3 Announce Type: replace-cross Abstract: Solutions of bilevel optimization problems tend to suffer from instability under changes to problem data. In the optimistic setting, we constr