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MarginGate: Sparse Margin-Triggered Verification for Batch-Invariant LLM Inference

model-releasesarxiv-cs-lg

arXiv:2605.30218v1 Announce Type: new Abstract: Temperature-zero BF16 LLM inference is often treated as reproducible, yet the same request can emit different tokens when decoded alone or inside a larg

Content type

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MARS Policy: Multimodality Only When It Matters

DGX agent

arXiv:2605.29766v1 Announce Type: new Abstract: Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to captur

safetyarxiv-cs-ro

29 May 2026

MARTIAN: A Rendering Framework for Aerial Mars Imagery from HiRISE Orbital Data

arXiv:2605.29647v1 Announce Type: new Abstract: Aerial navigation on Mars requires vision-based pipelines that are robust to the diverse illumination conditions and terrain morphology of the Martian s

Mask the Target: A Plug-and-Play Regularizer Against LoRA Forgetting

arXiv:2605.29498v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become one of the most widely used fine-tuning mechanisms for adapting large language models to new domains, tasks, and u

Masked Diffusion Modeling for Anomaly Detection

arXiv:2605.30046v1 Announce Type: cross Abstract: Anomaly detection aims to identify samples that deviate from the nominal data distribution and is central to many safety-critical applications. Howeve

safetyarxiv-cs-ai

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

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

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

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

safetyarxiv-cs-lg

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

Industry

MediaTek says it has started to use Intel Foundry's advanced chip packaging in addition to TSMC's, as the mobile chip designer bets on AI demand for growth (Cheng Ting-Fang/Nikkei Asia)

Cheng Ting-Fang / Nikkei Asia: MediaTek says it has started to use Intel Foundry's advanced chip packaging in addition to TSMC's, as the mobile chip designer bets on AI demand for growth — TAIPEI — Me

industrytechmeme

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

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

safetyarxiv-cs-cv

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

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

Applications

Miami-based Canals, which uses AI to help distributors automate workflows across sales, customer service, and more, raised a $35M Series A led by Base10 (Chris Metinko/Axios)

Chris Metinko / Axios: Miami-based Canals, which uses AI to help distributors automate workflows across sales, customer service, and more, raised a 35M Series A led by Base10 — Canals raised a 35 mill

applicationstechmeme

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

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

Applications

Microsoft faces backlash after a blog post implied criminal referral and legal action against security researcher Nightmare Eclipse over public bug disclosures (Lorenzo Franceschi-Bicchierai/TechCrunch)

Lorenzo Franceschi-Bicchierai / TechCrunch: Microsoft faces backlash after a blog post implied criminal referral and legal action against security researcher Nightmare Eclipse over public bug disclosu

applicationstechmeme

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

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

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