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Masked Diffusion Vision-Language Models for Temporal Action Localization

arXiv:2605.29858v1 Announce Type: new Abstract: Temporal action localization (TAL) requires recognizing the target event and localizing its start and end times precisely in untrimmed videos. Recent vi

researcharxiv-cs-cv

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MATANet: A Multi-context Attention and Taxonomy-Aware Network for Fine-Grained Underwater Recognition of Marine Species

DGX agent

arXiv:2601.03729v2 Announce Type: replace Abstract: Fine-grained recognition of marine organisms is important for ecological research, biodiversity monitoring, habitat conservation, and evidence-based

safetyarxiv-cs-cv

29 May 2026

Matching Rates and Optimal Allocation for Federated Probe-Logit Distillation under Heterogeneous Bandwidth Budgets

arXiv:2605.29642v1 Announce Type: cross Abstract: In federated language modeling, K nodes each hold n samples but cannot pool data or exchange full-precision gradients or weights. We study the minimax

MATNet: Multi-Level Fusion Transformer-Based Model for Day-Ahead PV Generation Forecasting

arXiv:2306.10356v3 Announce Type: replace-cross Abstract: Accurate forecasting of renewable generation is crucial to facilitate the integration of Renewable Energy Sources into the power system. Focus

Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms

arXiv:2401.08197v3 Announce Type: replace Abstract: This paper considers the problem of completing a rating matrix based on sub-sampled matrix entries as well as observed social graphs and hypergraphs

Agents

mcp-proto-okn: Natural-language access to open scientific knowledge graphs through the Model Context Protocol

arXiv:2605.30283v1 Announce Type: new Abstract: MCP Server Proto-OKN (mcp-proto-okn) is a Python-based Model Context Protocol server that enables AI assistants to discover, inspect, query and integrat

agentsarxiv-cs-ai

Mean-Field Diffuser: Scaling Offline MARL to Thousands of Agents

arXiv:2605.30190v1 Announce Type: new Abstract: Diffusion-based planning has achieved strong results in single-agent offline reinforcement learning, yet scaling to many-agent systems remains intractab

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Measure flow path recovery in Bayes Hilbert spaces

arXiv:2603.20329v2 Announce Type: replace-cross Abstract: We study the ill-posed problem of recovering a probability measure flow from finitely many moving localized sensors using a Bayes Hilbert fram

Applications

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening

arXiv:2605.28999v1 Announce Type: cross Abstract: LLMs are vulnerable to prompt injection attacks. However, this vulnerability has been primarily demonstrated conceptually in academic studies or throu

applicationsarxiv-cs-ai

MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation

arXiv:2604.05446v2 Announce Type: replace-cross Abstract: Obtaining high-quality labels is costly, whereas unlabeled covariates are often abundant, motivating semi-supervised inference methods with re

Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models

arXiv:2601.14758v4 Announce Type: replace-cross Abstract: Post-training pretrained autoregressive models (ARMs) into masked diffusion models (MDMs) has emerged as a cost-effective way to overcome the

Mechanistic origins of catastrophic forgetting: why RL preserves circuits better than SFT?

arXiv:2605.28860v1 Announce Type: cross Abstract: Fine-tuning large language models (LLMs) frequently induces catastrophic forgetting of prior capabilities. Recent work has shown that reinforcement le

MechELK: A Mechanistic Interpretability Framework for Eliciting Latent Knowledge in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.28825v1 Announce Type: new Abstract: Large language models (LLMs) frequently encode factual and reasoning knowledge in their internal representations that is not faithfully reflected in the

MedCase-Structured: A Text-to-FHIR Dataset for Benchmarking Diagnostic Reasoning in Clinically Realistic EHR Settings

arXiv:2605.30295v1 Announce Type: cross Abstract: Large language models (LLMs) show promise for clinical reasoning and decision support, but evaluation in realistic, electronic health record-congruent

Local Ai

MediHive: A Decentralized Agent Collective for Medical Reasoning

arXiv:2603.27150v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized medical reasoning tasks, yet single-agent systems often falter on complex, interdisciplinary proble

local-aiarxiv-cs-ai

MELD: Mel-Spectrogram-Based Speech Language Modeling with Discrete Latent Variables

arXiv:2605.29859v1 Announce Type: cross Abstract: Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downs

researcharxiv-cs-cl

Agents

MemCollab: Cross-Model Memory Collaboration via Contrastive Trajectory Distillation

arXiv:2603.23234v2 Announce Type: replace Abstract: LLM agents increasingly rely on memory mechanisms to reuse knowledge from past problem-solving experiences. However, existing methods typically cons

agentsarxiv-cs-ai

Tutorials

MEMENTO: Leveraging Web as a Learning Signal for Low-Data Domains

arXiv:2605.29795v1 Announce Type: new Abstract: Real-world tasks often lack large labeled datasets, motivating extensive work on learning in low-data regimes. However, existing approaches such as few-

tutorialsarxiv-cs-ai

MemoSight: Unifying Context Compression and Multi Token Prediction for Reasoning Acceleration

arXiv:2604.14889v2 Announce Type: replace Abstract: While chain-of-thought (CoT) reasoning enables LLMs to solve challenging reasoning tasks, the linear growth of the KV cache leads to substantial mem

MENTOR: Efficient Multimodal-Conditioned Tuning for Autoregressive Vision Generation Models

arXiv:2507.09574v3 Announce Type: replace-cross Abstract: Recent text-to-image models produce high-quality results but still struggle with precise visual control, balancing multimodal inputs, and requ

Mesh-Aware Epipolar Matching for Multi-View Multi-Person 3D Pose Estimation in Basketball

arXiv:2605.29953v1 Announce Type: new Abstract: Multi-view multi-person 3D pose estimation in team sports scenarios remains challenging due to player occlusions, appearance similarity caused by team u

researcharxiv-cs-cv

Local Ai

Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents

arXiv:2605.30159v1 Announce Type: new Abstract: Memory-augmented LLM agents tackle complex long-horizon tasks by recursively summarizing interaction trajectories into compact memory. However, existing

local-aiarxiv-cs-ai

Meta-Programming for Linear-time Temporal Answer Set Programming

arXiv:2605.29965v1 Announce Type: new Abstract: The development of temporal extensions of Answer Set Programming (ASP) has led to the emergence of non-monotonic linear-time (TEL), dynamic (DEL), and m

MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality

arXiv:2605.29212v1 Announce Type: new Abstract: Image quality in modern imaging systems emerges from the coupled effects of the sensor, optics, and computational reconstruction. Ultra-thin metalenses

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Metric-Dependent Annotation Saturation for Learning from Label Distributions

arXiv:2605.29797v1 Announce Type: new Abstract: When annotators disagree on a label, the disagreement itself carries signal -- and the number of annotators needed to capture it depends on the evaluati

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MiAD: Mirage Atom Diffusion for De Novo Crystal Generation

arXiv:2511.14426v2 Announce Type: replace-cross Abstract: In recent years, diffusion-based models have demonstrated exceptional performance in searching for simultaneously stable, unique, and novel (S

MIC: Maximizing Informational Capacity in Adaptive Representations via Isotropic Subspace Alignment

arXiv:2605.29987v1 Announce Type: cross Abstract: Although multi-scales representation learning enables elastic-dimension embeddings, nested subspaces often suffer from dimensional redundancy and spec

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Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models

arXiv:2605.28828v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve impressive performance across many tasks but remain prone to hallucination, especially in long-form generation wh

Midpoint Generative Models

arXiv:2605.29920v1 Announce Type: new Abstract: We introduce Midpoint Generative Models (MGM), a principled framework for training one-step generative models. MGM is based on a simple symmetry of Flow

Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion

arXiv:2605.29591v1 Announce Type: new Abstract: Modeling the interplay between external stimuli and internal neural representations is a pivotal research area for Brain-Computer Interfaces (BCIs). A m

Mind Your Tone: Does Tone Alter LLM Performance?

arXiv:2605.29027v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) is proliferating, yet their performance is observed to vary based on prompting styles and tones. In this study,

Agents

MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs

arXiv:2605.29512v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended intera

agentsarxiv-cs-ai

Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding

arXiv:2512.17220v2 Announce Type: replace Abstract: Humans understand long and complex texts by relying on a holistic semantic representation of the content. This global view helps organize prior know

researcharxiv-cs-cl

Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs

model-releasesarxiv-cs-cl

arXiv:2605.29737v1 Announce Type: cross Abstract: LLM-based coding assistants are seeing rapid adoption, offering substantial gains in developer productivity. As organizations increasingly ship code t

Mining or Synthesis? Rethinking Exploration Efficiency in Iterative Alignment of Mathematical Reasoning

arXiv:2602.05370v3 Announce Type: replace Abstract: Iterative Direct Preference Optimization (DPO) has emerged as a widely used paradigm for aligning Large Language Models on reasoning tasks. Existing

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minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models

arXiv:2605.30263v1 Announce Type: new Abstract: Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive

researcharxiv-cs-cv

MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection

arXiv:2605.30288v1 Announce Type: new Abstract: Mid-training has become an important stage in modern LLM development, using large-scale curated mixtures to strengthen capabilities before final post-tr

MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models

arXiv:2605.29360v1 Announce Type: new Abstract: Action-conditioned world models are increasingly used as scalable simulators for robot learning, yet current evaluations provide limited evidence that t

MIRAGE: Adaptive Multimodal Gating for Whole-Brain fMRI Encoding

arXiv:2605.29850v1 Announce Type: new Abstract: Recent progress in task-optimized neural networks has established encoding models as a powerful tool for predicting brain responses to naturalistic stim

Mitigating Hallucination in Vision-Language Models through Barrier-Regulated Adaptive Closed-form Steering

arXiv:2605.29881v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate objects that are not present in the input image, largely because visual grounding weakens as de

Mitigating State Aliasing in Vision-Language-Action Models via Inverse Dynamics Learning

arXiv:2605.29577v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a promising framework that unifies perception, reasoning, and control for robot manipulation by adap

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Mitigating Stethoscope-Induced Shortcuts in Respiratory Sound Classification under Federated Domain Generalization with Causality-Inspired Interventions

arXiv:2605.29862v1 Announce Type: cross Abstract: AI-driven respiratory sound classification (RSC) is promising for automated pulmonary disease detection, yet multi-site deployment is hindered by inte

Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context

arXiv:2510.06182v2 Announce Type: replace Abstract: A key component of in-context reasoning is the ability of language models (LMs) to bind entities for later retrieval. For example, an LM might repre

researcharxiv-cs-cl

Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming

arXiv:2605.29329v1 Announce Type: cross Abstract: A novel two-phase molecule inference framework, mol-infer, has recently been developed to infer chemical graphs with prescribed abstract structures an

MMTM: Tri-Modal Topic Modeling for Long-Form Video via Similarity-Gated Fusion

arXiv:2605.29765v1 Announce Type: new Abstract: We introduce MMTM, a modular pipeline for topic discovery in long-form video that integrates speech recognition, audio and visual embeddings, and BERTop

Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds

arXiv:2510.27391v2 Announce Type: replace Abstract: Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods e

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Model Fusion via Retrofitting

arXiv:2507.00037v2 Announce Type: replace-cross Abstract: Model fusion seeks to combine independently trained neural networks into a single model without retraining, but is complicated by representati

safetyarxiv-cs-ai

Model Merging by Output-Space Projection

arXiv:2605.29101v1 Announce Type: new Abstract: Model merging combines fine-tuned checkpoints into a single multi-task model without retraining. Existing methods - such as task arithmetic, model soups