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MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems

arXiv:2503.16549v2 Announce Type: replace Abstract: Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially

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MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and Retrieval

DGX agent

arXiv:2604.18584v1 Announce Type: cross Abstract: Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in

model-releasesarxiv-cs-lg

21 Apr 2026

Matlas: A Semantic Search Engine for Mathematics

arXiv:2604.17484v1 Announce Type: cross Abstract: Retrieving mathematical knowledge is a central task in both human-driven research, such as determining whether a result already exists, finding relate

researcharxiv-cs-lg

Agents

Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

agentsarxiv-cs-cl

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning

arXiv:2601.03190v3 Announce Type: replace Abstract: Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approac

MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning

arXiv:2604.16929v1 Announce Type: new Abstract: The accurate extraction of scientific measurements from literature is a critical yet challenging task in AI4Science, enabling large-scale analysis and i

Applications

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance

arXiv:2604.17650v1 Announce Type: new Abstract: LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, p

applicationsarxiv-cs-cl

Measuring Representation Robustness in Large Language Models for Geometry

arXiv:2604.16421v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains po

Measuring Social Bias in Vision-Language Models with Face-Only Counterfactuals from Real Photos

arXiv:2601.06931v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demog

Measuring the Gap Between Media Coverage and Public Information Demand: Evidence from the 2026 Lebanon Conflict

arXiv:2604.16417v1 Announce Type: cross Abstract: This study examines the relationship between media coverage and public information demand during the Lebanon conflict in March 2026. Using a dataset o

Mechanisms of Multimodal Synchronization: Insights from Decoder-Based Video-Text-to-Speech Synthesis

arXiv:2411.17690v3 Announce Type: replace-cross Abstract: Unified decoder-only transformers have shown promise for multimodal generation, yet the mechanisms by which they synchronize modalities with h

safetyarxiv-cs-cv

Medial Axis Aware Learning of Signed Distance Functions

arXiv:2604.16512v1 Announce Type: new Abstract: We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump s

Medical Image Understanding Improves Survival Prediction via Visual Instruction Tuning

arXiv:2604.18250v1 Announce Type: new Abstract: Accurate prognostication and risk estimation are essential for guiding clinical decision-making and optimizing patient management. While radiologist-ass

Medical thinking with multiple images

arXiv:2604.16506v1 Announce Type: cross Abstract: Large language models perform well on many medical QA benchmarks, but real clinical reasoning often requires integrating evidence across multiple imag

MEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition

arXiv:2604.17899v1 Announce Type: new Abstract: Unlike macro-expression, micro-expression does not follow a strictly consistent mapping rule between emotions and Action Units (AUs). As a result, some

MedPRMBench: A Fine-grained Benchmark for Process Reward Models in Medical Reasoning

arXiv:2604.17282v1 Announce Type: new Abstract: Process-Level Reward Models (PRMs) are essential for guiding complex reasoning in large language models, yet existing PRM benchmarks cover only general

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

arXiv:2604.18418v1 Announce Type: new Abstract: Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medici

MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health Communication

arXiv:2601.09853v2 Announce Type: replace Abstract: Real-world health questions from patients often unintentionally embed false assumptions or premises. In such cases, safe medical communication typic

MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation

arXiv:2512.20626v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to dynamically access external information, which is powerful for an

MemBuilder: Reinforcing LLMs for Long-Term Memory Construction via Attributed Dense Rewards

arXiv:2601.05488v3 Announce Type: replace Abstract: Maintaining consistency in long-term dialogues remains a fundamental challenge for LLMs, as standard retrieval mechanisms often fail to capture the

Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation

arXiv:2604.18215v1 Announce Type: new Abstract: Spatially consistent long-horizon video generation aims to maintain temporal and spatial consistency along predefined camera trajectories. Existing meth

tutorialsarxiv-cs-cv

Agents

Memory Centric Power Allocation for Multi-Agent Embodied Question Answering

arXiv:2604.17810v1 Announce Type: new Abstract: This paper considers multi-agent embodied question answering (MA-EQA), which aims to query robot teams on what they have seen over a long horizon. In co

agentsarxiv-cs-ro

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval

arXiv:2604.17054v1 Announce Type: new Abstract: Scalable Vector Graphics (SVGs) function both as visual images and as structured code that encode rich geometric and layout information, yet most method

MerLin: A Discovery Engine for Photonic and Hybrid Quantum Machine Learning

model-releasesarxiv-cs-lg

arXiv:2602.11092v2 Announce Type: replace Abstract: Identifying where quantum models may offer practical benefits in near term quantum machine learning (QML) requires moving beyond isolated algorithmi

MESA: A Training-Free Multi-Exemplar Deep Framework for Restoring Ancient Inscription Textures

arXiv:2604.17390v1 Announce Type: new Abstract: Ancient inscriptions frequently suffer missing or corrupted regions from fragmentation, erosion, or other damage, hindering reading, and analysis. We re

safetyarxiv-cs-cv

MeSH: Memory-as-State-Highways for Recursive Transformers

model-releasesarxiv-cs-lg

arXiv:2510.07739v2 Announce Type: replace Abstract: Recursive transformers reuse parameters and iterate over hidden states multiple times, decoupling compute depth from parameter depth. However, under

MetaCloak-JPEG: JPEG-Robust Adversarial Perturbation for Preventing Unauthorized DreamBooth-Based Deepfake Generation

arXiv:2604.18537v1 Announce Type: new Abstract: The rapid progress of subject-driven text-to-image synthesis, and in particular DreamBooth, has enabled a consent-free deepfake pipeline: an adversary n

MetaLint: Easy-to-Hard Generalization for Code Linting

arXiv:2507.11687v4 Announce Type: replace-cross Abstract: Large language models excel at code generation but struggle with code linting, particularly in generalizing to unseen or evolving best practic

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

arXiv:2602.11182v2 Announce Type: replace Abstract: Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions bey

tutorialsarxiv-cs-cl

Method for Aggregating Unstructured Data Using Large Language Models

model-releasesarxiv-cs-lg

arXiv:2604.16425v1 Announce Type: cross Abstract: This paper presents a method for the automated collection and aggregation of unstructured data from diverse web sources, utilizing Large Language Mode

MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models

arXiv:2604.17730v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored as scalable tools for mental health counseling, yet evaluating their safety remains challenging d

safetyarxiv-cs-cl

Migrant Voices, Local News: Insights on Bridging Community Needs with Media Content

arXiv:2604.16651v1 Announce Type: new Abstract: Research shows news consumption differs across demographics, yet little is known about non-mainstream audiences, especially in relation to local media.

Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs

arXiv:2603.02618v3 Announce Type: replace Abstract: Out-of-distribution (OOD) detection seeks to identify samples from unknown classes, a critical capability for deploying machine learning models in o

Local Ai

Mira-Embeddings-V1: Domain-Adapted Semantic Reranking for Recruitment via LLM-Synthesized Data

arXiv:2604.17738v1 Announce Type: new Abstract: Candidate sourcing for recruiters is best viewed as a two-stage retrieval and reranking pipeline with recall as the primary objective under a limited re

local-aiarxiv-cs-cl

Missing-by-Design: Certifiable Modality Deletion for Revocable Multimodal Sentiment Analysis

arXiv:2602.16144v3 Announce Type: replace Abstract: As multimodal systems increasingly process sensitive personal data, the ability to selectively revoke specific data modalities has become a critical

Missing Pattern Tree based Decision Grouping and Ensemble for Enhancing Pair Utilization in Deep Incomplete Multi-View Clustering

arXiv:2512.21510v2 Announce Type: replace-cross Abstract: Real-world multi-view data often exhibit highly inconsistent missing patterns, posing significant challenges for incomplete multi-view cluster

Mitigating Multimodal Hallucination via Phase-wise Self-reward

arXiv:2604.17982v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) still struggle with vision hallucination, where generated responses are inconsistent with the visual input. Exist

Mix and Match: Context Pairing for Scalable Topic-Controlled Educational Summarisation

arXiv:2604.18087v1 Announce Type: new Abstract: Topic-controlled summarisation enables users to generate summaries focused on specific aspects of source documents. This paper investigates a data augme

safetyarxiv-cs-cl

MLE-UVAD: Minimal Latent Entropy Autoencoder for Fully Unsupervised Video Anomaly Detection

arXiv:2603.23868v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of single-scene, fully unsupervised video anomaly detection (VAD), where raw videos containing bot

mlr3torch: A Deep Learning Framework in R based on mlr3 and torch

arXiv:2604.18152v1 Announce Type: cross Abstract: Deep learning (DL) has become a cornerstone of modern machine learning (ML) praxis. We introduce the R package mlr3torch, which is an extensible DL fr

tutorialsarxiv-cs-lg

MM-Hand: A 21-DOF Multi-modal Modular Dexterous Robotic Hand with Remote Actuation

arXiv:2604.17245v1 Announce Type: new Abstract: High-DOF dexterous hands require compact actuation, rich sensing, and reliable thermal behavior, but conventional designs often occupy valuable in-hand

tutorialsarxiv-cs-ro

MM-JudgeBias: A Benchmark for Evaluating Compositional Biases in MLLM-as-a-Judge

arXiv:2604.18164v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have been increasingly used as automatic evaluators-a paradigm known as MLLM-as-a-Judge. However, their reliabi

MMErroR: A Benchmark for Erroneous Reasoning in Vision-Language Models

arXiv:2601.03331v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have improved performance in multi-modal learning, raising the question of whether these models tru

MNAFT: modality neuron-aware fine-tuning of multimodal large language models for image translation

arXiv:2604.16943v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown impressive capabilities, yet they often struggle to effectively capture the fine-grained textual inf

MobileAgeNet: Lightweight Facial Age Estimation for Mobile Deployment

arXiv:2604.17007v1 Announce Type: new Abstract: Mobile deployment of facial age estimation requires models that balance predictive accuracy with low latency and compact size. In this work, we present

MoCo: A One-Stop Shop for Model Collaboration Research

arXiv:2601.21257v2 Announce Type: replace Abstract: Advancing beyond single monolithic language models (LMs), recent research increasingly recognizes the importance of model collaboration, where multi

safetyarxiv-cs-cl

Model in Distress: Sentiment Analysis on French Synthetic Social Media

arXiv:2604.18226v1 Announce Type: new Abstract: Automated analysis of customer feedback on social media is hindered by three challenges: the high cost of annotated training data, the scarcity of evalu

Modeling Biomechanical Constraint Violations for Language-Agnostic Lip-Sync Deepfake Detection

arXiv:2604.16808v1 Announce Type: new Abstract: Current lip-sync deepfake detectors rely on pixel-level artifacts or audio-visual correspondence, failing to generalize across languages because these c