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MC-Risk: Multi-Component Risk Fields for Risk Identification and Motion Planning

arXiv:2605.21406v1 Announce Type: new Abstract: We present MC-Risk, a planner-aligned, multi-component risk field on a bird's-eye-view grid that yields early, calibrated, and class-aware risk localiza

agentsarxiv-cs-ro

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Measuring and mitigating overreliance to build human-compatible AI

DGX agent

arXiv:2509.08010v2 Announce Type: replace-cross Abstract: Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable o

applicationsarxiv-cs-cl

21 May 2026

Mechanics of Bias and Reasoning: Interpreting the Impact of Chain-of-Thought Prompting on Gender Bias in LLMs

arXiv:2605.20410v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in socially sensitive settings despite substantial documentation that they encode gender biases.

Local Ai

Mechanisms of Misgeneralization in Physical Sequence Modeling

arXiv:2605.20299v1 Announce Type: new Abstract: Generative sequence models are often trained to plan motion in physical domains, from robotics to mechanical simulations. When constructing a dataset to

local-aiarxiv-cs-lg

Mechanistic Interpretability for Learning Assurance of a Vision-Based Landing System

arXiv:2605.20607v1 Announce Type: cross Abstract: EASA's learning-assurance guidance requires data-driven aviation systems to build and monitor their own situation representation, yet for neural netwo

safetyarxiv-cs-cv

MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery

model-releasesarxiv-cs-cv

arXiv:2605.20297v1 Announce Type: new Abstract: Medical image segmentation faces a fundamental challenge in continual learning: data arrives sequentially from heterogeneous sources, yet effective cont

MedicalBench: Evaluating Large Language Models Toward Improved Medical Concept Extraction

arXiv:2605.20197v1 Announce Type: new Abstract: Medical concept extraction from electronic health records underpins many downstream applications, yet remains challenging because medically meaningful c

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Cod…

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Coding agent, end to end. Frontend prototypes, multi-file refactor

model-releasesqwen--x

Mem-pi: Adaptive Memory through Learning When and What to Generate

arXiv:2605.21463v1 Announce Type: new Abstract: We present Mem-pi, a framework for adaptive memory in large language model (LLM) agents, where useful guidance is generated on demand rather than retrie

agentsarxiv-cs-cl

MemGym: a Long-Horizon Memory Environment for LLM Agents

arXiv:2605.20833v1 Announce Type: new Abstract: Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of person

Tutorials

Memorisation, convergence and generalisation in generative models

arXiv:2605.21402v1 Announce Type: cross Abstract: Generative neural networks learn how to produce highly realistic images from a large, but finite number of examples - or do they simply memorise their

tutorialsarxiv-cs-lg

Memory-Efficient Partitioned DNN Inference on Resource-Constrained Android Crowds

model-releasesarxiv-cs-lg

arXiv:2605.20723v1 Announce Type: new Abstract: Deploying large deep neural networks on memory-constrained mobile devices is a central challenge in edge ML. While compression, pruning, and quantizatio

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory

arXiv:2605.20948v1 Announce Type: new Abstract: Scaling conditional memory offers a promising way to increase language-model capacity, but existing methods such as Engram learn large memory tables fro

Mercer Large-Scale Kernel Machines from Ridge Function Perspective

arXiv:2307.11925v3 Announce Type: replace Abstract: To present Mercer large-scale kernel machines from a ridge function perspective, we recall the results by Lin and Pinkus from {it Fundamentality of

MeshTailor: Cutting Seams via Generative Mesh Traversal

arXiv:2603.27309v2 Announce Type: replace-cross Abstract: We present MeshTailor, the first mesh-native generative framework for synthesizing edge-aligned seams on 3D surfaces. Unlike prior optimizatio

researcharxiv-cs-cv

Meta lays off thousands of employees to offset AI investments

Meta has reportedly notified thousands of employees that they've been laid off as the company attempts to compensate for its hefty AI investments. In an email from Meta management shared by Business I

industrythe-verge-ai

Metaphors in Literary Post-Editing: Opening Pandora's Box?

arXiv:2605.21178v1 Announce Type: new Abstract: This paper investigates how post-editors of literary texts react and respond to the way metaphors have been translated by Neu ral Machine Translation (N

researcharxiv-cs-cl

🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with …

model-releasesyann-lecun--x

🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an inte

Miller-Index-Based Latent Crystallographic Fracture Plane Reasoning with Vision-Language Models

arXiv:2605.20416v1 Announce Type: new Abstract: We study whether multimodal large language models (MLLMs) can leverage crystallographic plane indices (Miller indices) as a structured latent representa

applicationsarxiv-cs-lg

Mind the Sim-to-Real Gap & Think Like a Scientist

arXiv:2605.21458v1 Announce Type: cross Abstract: Suppose a planner has a pre-trained simulator of a sequential decision problem and the option to run real experiments in the field. The simulator is c

Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?

arXiv:2605.20606v1 Announce Type: new Abstract: Dataset distillation (DD) compresses a large training set into a small synthetic set for efficient training, but most DD methods optimize only clean acc

researcharxiv-cs-cv

Mitigating Label Bias with Interpretable Rubric Embeddings

arXiv:2605.21455v1 Announce Type: new Abstract: Statistical decision algorithms are increasingly deployed in domains where ground-truth labels are hard to obtain, such as hiring, university admissions

Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs

arXiv:2605.20315v1 Announce Type: new Abstract: LLM agents have recently emerged as a powerful paradigm for solving complex tasks through planning, tool use, memory retrieval, and multi-step interacti

agentsarxiv-cs-cl

Mobile UMI: Cross-View Diffusion Policy with Decoupled Kinematics for Mobile Manipulation

arXiv:2605.20894v1 Announce Type: new Abstract: Mobile imitation learning on portable demonstration interfaces faces two coupled bottlenecks: locomotion-contaminated action labels and inference-induce

safetyarxiv-cs-ro

Local Ai

Modality-Decoupled Online Recursive Editing

arXiv:2605.20273v1 Announce Type: new Abstract: Online model editing for multimodal large language models (MLLMs) requires assimilating a stream of corrections under tight compute and memory budgets.

local-aiarxiv-cs-lg

Modeling and Control of a Pneumatic Morphing Soft Quadrotor based on the SOFA Framework for Dynamic Soft Robotic Simulation

arXiv:2605.21031v1 Announce Type: new Abstract: This article presents a novel SOFA based finite element method for the soft body modeling and the corresponding dynamic simulation and control of a pneu

researcharxiv-cs-ro

Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport

arXiv:2605.20989v1 Announce Type: new Abstract: Single-cell RNA sequencing provides insights into gene expression at single-cell resolution, yet inferring temporal processes from these static snapshot

Modular Multimodal Classification Without Fine-Tuning: A Simple Compositional Approach

arXiv:2605.20674v1 Announce Type: new Abstract: We introduce CoMET, extit{extbf{C}omposing extbf{M}odality extbf{E}ncoders with extbf{T}abular foundation models}, a simple yet highly competitive metho

MONET: A Massive, Open, Non-redundant and Enriched Text-to-image dataset

model-releasesarxiv-cs-cv

arXiv:2605.21272v1 Announce Type: new Abstract: Training large text-to-image models requires high-quality, curated datasets with diverse content and detailed captions. Yet the cost and complexity of c

Most Transformer Modifications Still Do Not Transfer at 1-3B: A 2020-2026 Update to Narang et al. (2021) with Downstream Evaluation and a Noise Floor

arXiv:2605.20798v1 Announce Type: cross Abstract: Narang et al. (2021) evaluated 40+ Transformer modifications at T5-base scale and concluded that most did not transfer. Five years later, the typical

researcharxiv-cs-cl

Motion-Robust Deep Reconstruction for Free-Breathing Cardiac Cine MRI

arXiv:2605.20687v1 Announce Type: cross Abstract: Conventional cardiac cine MRI relies on breath-hold Cartesian acquisitions, which are vulnerable to motion artifacts and can be uncomfortable or infea

Move fast, break nothing: How Forward Predict brings CI/CD discipline to networking

Startup Forward Inc. today rolled out Forward Predict, software that lets customers model the impact of network changes before changes go live. Rather than a routine feature update in a crowded artifi

industrysiliconangle

MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks

arXiv:2605.20729v1 Announce Type: new Abstract: Accurate evaluation of conversational retrieval is pivotal for advancing Retrieval-Augmented Generation (RAG) systems. However, existing conversational

Multi-agent Collaboration with State Management

arXiv:2605.20563v1 Announce Type: cross Abstract: Recent advances in multi-agent systems have shown great potential for solving complex tasks. However, when multiple agents edit a shared codebase conc

agentsarxiv-cs-cl

Multi-Agent Reinforcement Learning for Safe Autonomous Driving Under Pedestrian Behavioral Uncertainty

arXiv:2605.20255v1 Announce Type: new Abstract: Simulation-based testing of self-driving cars (SDCs) typically relies on scripted or simplified pedestrian models that do not capture the heterogeneity

Multi-Channel Replay Speech Detection using Acoustic Maps

arXiv:2602.16399v2 Announce Type: replace-cross Abstract: Replay attacks remain a critical vulnerability for automatic speaker verification systems, particularly in real-time voice assistant applicati

Multi-Head Attention as Ensemble Nadaraya-Watson Estimation: Variance Reduction, Decorrelation, and Optimal Head Diversity

arXiv:2605.20271v1 Announce Type: cross Abstract: We develop a rigorous statistical theory of multi-head attention (MHA) as an ensemble of Nadaraya-Watson (NW) kernel regression estimators. Building o

Local Ai

Multi-needle Localization for Pelvic Seed Implant Brachytherapy based on Tip-handle Detection and Matching

arXiv:2509.17931v2 Announce Type: replace Abstract: Accurate multi-needle localization in intraoperative CT images is crucial for optimizing seed placement in pelvic seed implant brachytherapy. Howeve

local-aiarxiv-cs-cv

Multi-Step Likelihood-Ratio Correction for Reinforcement Learning with Verifiable Rewards

arXiv:2605.20865v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) plays a pivotal role in improving the reasoning ability of large language models. However, widely

Multi-Week, In-Class Deployments of Telepresence Robots With Four Homebound K-12 Students: Benefits, Challenges, and Recommendations

arXiv:2605.20431v1 Announce Type: cross Abstract: Missing significant amounts of school during K-12 education is known to put students' cognitive and social development at risk. Alternatives such as h

applicationsarxiv-cs-ro

Multimodal Fusion for Sim2real Transfer in Visual Reinforcement Learning

arXiv:2507.09180v4 Announce Type: replace Abstract: Depth information is robust to scene appearance variations and inherently carries 3D spatial details. Thus, a visual backbone based on the vision tr

applicationsarxiv-cs-cv

Multimodal LLMs under Pairwise Modalities

arXiv:2605.21059v1 Announce Type: new Abstract: Despite the impressive results achieved by multimodal large language models (MLLMs), their training typically relies on jointly curated multimodal data,

safetyarxiv-cs-cv

Multimodal Optimal Transport for Training-free Temporal Segmentation in Surgical Robotics

model-releasesarxiv-cs-cv

arXiv:2602.24138v2 Announce Type: replace Abstract: Automated recognition of surgical phases and steps is a fundamental capability for intraoperative decision support, workflow automation, and skill a

Musical Attention Transformer: Music Generation Using a Music-Specific Attention Model

arXiv:2605.21081v1 Announce Type: cross Abstract: This study aims to enhance the quality of music generation using Transformers by incorporating meta-information. While Transformer-based approaches ar

Musk v. Altman: Much ado about nothing

Today I’m talking with Liz Lopatto, who spent the last month covering the Musk v. Altman trial in all its chaos. You’ll hear her describe the courthouse as a “zoo” and explain that there were protests

industrythe-verge-ai

NaP-Control: Navigating Diffusion Prior for Versatile and Fast Character Control

arXiv:2605.20209v1 Announce Type: cross Abstract: Achieving precise, versatile whole-body character control in physics-based animation remains challenging. Recent diffusion-based policies generate ric

Narrow math speciality counts for a lot of things! A physics example: Many have studied special relativity. How many know or have computed t…

Narrow math speciality counts for a lot of things! A physics example: Many have studied special relativity. How many know or have computed the Killing Form of the space time algebra? If you do then yo

industryemad-mostaque--x

Tutorials

Nathan's @cursor_ai team didn't prompt-engineer their way to Composer 2.5. They trained it. The massive RL program runs RL rollouts on Firew…

Nathan's @cursor_ai team didn't prompt-engineer their way to Composer 2.5. They trained it. The massive RL program runs RL rollouts on Fireworks, alongside production inference. 'Comment 🔥 to see my p

tutorialsfireworks-ai--x