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arXiv:2605.08670v1 Announce Type: new Abstract: Large language model (LLM) powered AI agents have emerged as a promising paradigm for autonomous problem-solving, yet they continue to struggle with com

agentsarxiv-cs-ai

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Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer

DGX agent

arXiv:2602.12286v2 Announce Type: replace-cross Abstract: A central challenge in developing Multimodal Large Language Models (MLLMs) is effectively integrating heterogeneous inputs into a cohesive rea

researcharxiv-cs-cl

12 May 2026

MineEvolve: Self-Evolution with Accumulated Knowledge for Long-Horizon Embodied Minecraft Agents

arXiv:2603.13131v3 Announce Type: replace Abstract: Long-horizon embodied intelligence requires agents to improve through interaction, not merely to execute plans generated from static goals. A centra

Minimal Filling Architectures of Polynomial Neural Networks: Counterexamples, Frontier Search, and Defects

arXiv:2605.09609v1 Announce Type: new Abstract: We provide a counterexample to the minimal unimodal conjecture for polynomial neural networks (PNNs) with power activation functions. Fixing the input a

Minimizing Worst-Case Weighted Latency for Multi-Robot Persistent Monitoring: Theory and RL-Based Solutions

model-releasesarxiv-cs-ro

arXiv:2605.09633v1 Announce Type: new Abstract: We study multi-robot persistent monitoring on weighted graphs, where node weights encode monitoring priorities and edge weights encode travel distances.

Mirror, Mirror on the Wall: Can VLM Agents Tell Who They Are at All?

arXiv:2605.08816v1 Announce Type: new Abstract: In the animal kingdom, mirror self-recognition is a canonical probe of higher-order cognition, emerging only in some species. We ask whether an analogou

Mismatch-Aware Adaptive Constraint Tightening for Bicycle-Model Trajectory Optimization

arXiv:2605.09376v1 Announce Type: new Abstract: Trajectory optimization for autonomous vehicles usually relies on the kinematic bicycle model because of its computational simplicity. However, when the

safetyarxiv-cs-ro

Mistake-Bounded Language Generation

arXiv:2605.10809v1 Announce Type: new Abstract: We investigate the learning task of language generation in the limit, but shift focus from the traditional time-of-last-mistake metric of a generator's

Mitigating Data Scarcity in Spaceflight Applications for Offline Reinforcement Learning Using Physics-Informed Deep Generative Models

arXiv:2604.02438v2 Announce Type: replace Abstract: The deployment of reinforcement learning (RL)-based controllers on physical systems is often limited by poor generalization to real-world scenarios,

safetyarxiv-cs-lg

Mitigating Many-shot Jailbreak Attacks with One Single Demonstration

arXiv:2605.08277v1 Announce Type: cross Abstract: Many-shot jailbreaking (MSJ) causes safety-aligned language models to answer harmful queries by preceding them with many harmful question-answer demon

Mitigating Membership Inference in Intermediate Representations with Differentially Private Training

arXiv:2602.22611v2 Announce Type: replace Abstract: In Embedding-as-an-Interface (EaaI) settings, pre-trained models are queried for Intermediate Representations (IRs). The distributional properties o

Mitigating Watermark Forgery in Generative Models via Randomized Key Selection

arXiv:2507.07871v4 Announce Type: replace-cross Abstract: Watermarking enables GenAI providers to verify whether content was generated by their models. A watermark is a hidden signal in the content, w

Mixture of Experts for Recognizing Depression from Interview and Reading Tasks

arXiv:2502.20213v2 Announce Type: replace Abstract: Depression is a mental disorder and can cause a variety of symptoms, including psychological, physical, and social. Speech has been proved an object

Mixture of Layers with Hybrid Attention

arXiv:2605.09516v1 Announce Type: cross Abstract: Standard Mixture-of-Experts (MoE) transformers route tokens to expert subnetworks within each layer, but the layer structure itself remains monolithic

ML-CLIPSim: Multi-Layer CLIP Similarity for Machine-Oriented Image Quality

arXiv:2605.09479v1 Announce Type: cross Abstract: We study full-reference image quality assessment from a machine-centric perspective, where images are evaluated by how well they preserve information

MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI

model-releasesarxiv-cs-lg

arXiv:2605.08678v1 Announce Type: new Abstract: Modern AI progress has been driven by ML methods that are generalizable across settings and scalable to larger regimes. As large language models demonst

MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection

arXiv:2605.10833v1 Announce Type: cross Abstract: Industrial anomaly detection is critical for manufacturing quality control, yet existing datasets mainly focus on static images or sparse views, which

MOBIUS: A Multi-Modal Bipedal Robot that can Walk, Crawl, Climb, and Roll

arXiv:2511.01774v3 Announce Type: replace Abstract: This paper presents the MOBIUS platform, a bipedal robot capable of walking, crawling, climbing, and rolling. MOBIUS features four limbs, two 6-DoF

researcharxiv-cs-ro

Hardware

Model-Aware Tokenizer Transfer

arXiv:2510.21954v2 Announce Type: replace Abstract: Large Language Models (LLMs) are trained to support an increasing number of languages, yet their predefined tokenizers remain a bottleneck for adapt

hardwarearxiv-cs-cl

Model-based Dynamic 3D MRI Reconstructions using Neural Fields and Tensor Product Expansions

arXiv:2605.08275v1 Announce Type: cross Abstract: Conventional MRI reconstruction methods treat images and coil sensitivities as discrete objects, leading to high memory demands and limited structural

Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds

model-releasesarxiv-cs-lg

arXiv:2605.09724v1 Announce Type: new Abstract: Existing accounts of grokking explain the phenomena in terms of mechanistic frameworks such as circuit efficiency or lazy-to-rich transitions. However,

Model-Free Neural Filtering: A Comparison with Classical Filters in Nonlinear Systems

model-releasesarxiv-cs-lg

arXiv:2601.21266v3 Announce Type: replace Abstract: Neural network models are increasingly used for state estimation in control and decision-making, yet it remains unclear to what extent they behave a

Model Merging Scaling Laws in Large Language Models

arXiv:2509.24244v4 Announce Type: replace Abstract: We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative r

Model-Reference Adaptive Flight Control of the 95-mg Bee++

arXiv:2605.08525v1 Announce Type: new Abstract: We introduce a model-reference adaptive control (MRAC) architecture for high-performance positional tracking of the Bee++, a 95-mg insect-scale flapping

researcharxiv-cs-ro

Modeling Atomic Conformational Ensembles of Proteins via Test-Time Supervision of Boltz-2 on Cryo-EM Density Maps

arXiv:2605.09832v1 Announce Type: new Abstract: Knowledge of a protein's atomic conformational ensemble is critical to determining its function, yet state-of-the-art ensemble prediction models are lim

Applications

Modular Retrieval-Augmented Generalization for Human Action Recognition

arXiv:2605.08117v1 Announce Type: cross Abstract: Inertial Measurement Unit (IMU)-based Human Activity Recognition (HAR) aims to interpret and classify user behaviors from temporal motion signals. Rec

applicationsarxiv-cs-cv

MolRGen: A Training and Evaluation Setting for De Novo Molecular Generation with Reasonning Models

arXiv:2603.18256v2 Announce Type: replace-cross Abstract: Recent reasoning-based large language models have shown strong performance on tasks with verifiable outcomes, but their use in de novo molecul

MolSight: Molecular Property Prediction with Images

model-releasesarxiv-cs-cl

arXiv:2605.10157v1 Announce Type: cross Abstract: Every molecule ever synthesised can be drawn as a 2D skeletal diagram, yet in modern property prediction this universally available representation has

Local Ai

MolWorld: Molecule World Models for Actionable Molecular Optimization

arXiv:2605.08954v1 Announce Type: cross Abstract: Molecular optimization in drug discovery aims to discover molecules with improved target properties, but practical lead optimization often requires mo

local-aiarxiv-cs-ai

MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning

arXiv:2605.08512v1 Announce Type: new Abstract: Temporally contrastive representation learning induces a latent structure capable of reducing long-horizon planning to inference in a low-dimensional li

safetyarxiv-cs-lg

MonitoringBench: Semi-Automated Red-Teaming for Agent Monitoring

arXiv:2605.09684v1 Announce Type: cross Abstract: We introduce a red-teaming methodology that exposes harder-to-catch attacks for coding-agent monitors, suggesting that current practices may under-eli

Monocular Biomechanical Tracking of Fingers with Inverse Kinematics to Foundation Models

arXiv:2605.09258v1 Announce Type: cross Abstract: Accurate hand and finger tracking from video has significant clinical applications for monitoring activities of daily living and measuring range of mo

MoPO: Incorporating Motion Prior for Occluded Human Mesh Recovery

arXiv:2605.09856v1 Announce Type: cross Abstract: Although recent studies have made remarkable progress in human mesh recovery, they still exhibit limited robustness to occlusions and often produce in

Morphology-Aware Graph Reinforcement Learning for Tensegrity Robot Locomotion

arXiv:2510.26067v2 Announce Type: replace Abstract: Tensegrity robots combine rigid rods and elastic cables, offering high resilience and deployability but at the same time posing major challenges for

safetyarxiv-cs-ro

MOTOR-Bench: A Real-world Dataset and Multi-agent Framework for Zero-shot Human Mental State Understanding

model-releasesarxiv-cs-cv

arXiv:2605.09703v1 Announce Type: new Abstract: Understanding human mental states from natural behavior is crucial for intelligent systems in the real world. However, most current research focuses on

MPerS: Dynamic MLLM MixExperts Perception-Guided Remote Sensing Scene Segmentation

arXiv:2605.10769v1 Announce Type: cross Abstract: The multimodal fusion of images and scene captions has been extensively explored and applied in various fields. However, when dealing with complex rem

MTA-RL: Robust Urban Driving via Multi-modal Transformer-based 3D Affordances and Reinforcement Learning

arXiv:2605.10177v1 Announce Type: cross Abstract: Robust urban autonomous driving requires reliable 3D scene understanding and stable decision-making under dense interactions. However, existing end-to

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image

model-releasesarxiv-cs-cl

arXiv:2605.10616v1 Announce Type: cross Abstract: Tabular Foundation Models have recently established the state of the art in supervised tabular learning, by leveraging pretraining to learn generaliza

Multi-Armed Bandits With Best-Action Queries

arXiv:2605.08287v1 Announce Type: cross Abstract: We study multi-armed bandits (MABs) augmented with best-action queries, in which the learner may additionally query an oracle that reveals the best ar

Multi-domain Multi-modal Document Classification Benchmark with a Multi-level Taxonomy

model-releasesarxiv-cs-cl

arXiv:2605.10550v1 Announce Type: new Abstract: Document classification forms the backbone of modern enterprise content management, yet existing benchmarks remain trapped in oversimplified paradigms -

Multi-layer attentive probing improves transfer of audio representations for bioacoustics

arXiv:2605.10494v1 Announce Type: cross Abstract: Probing heads map the representations learned from audio by a machine learning model to downstream task labels and are a key component in evaluating r

Multi-Level Graph Attention Network Contrastive Learning for Knowledge-Aware Recommendation

arXiv:2605.08499v1 Announce Type: cross Abstract: In recent years, the use of edge information provided by knowledge graphs together with the advantages of higher-order connectivity in graph neural ne

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning

arXiv:2605.09364v1 Announce Type: new Abstract: This paper investigates robust representation learning in offline goal-conditioned reinforcement learning (GCRL). Particularly in sparse reward scenario

safetyarxiv-cs-lg

Multi-Tier Labeling and Physics-Informed Learning for Orbital Anomaly Detection at Scale

arXiv:2605.09790v1 Announce Type: cross Abstract: Detecting orbital anomalies, such as maneuvers, atmospheric decay, and attitude upsets, across the rapidly growing population of low-Earth-orbit (LEO)

MultiAnimate: Pose-Guided Image Animation Made Extensible

arXiv:2602.21581v2 Announce Type: replace Abstract: Pose-guided human image animation aims to synthesize realistic videos of a reference character driven by a sequence of poses. While diffusion-based

Multifidelity Gaussian process regression for solving nonlinear partial differential equations

arXiv:2605.10383v1 Announce Type: cross Abstract: Solving nonlinear partial differential equations (PDEs) using kernel methods offers a compelling alternative to traditional numerical solvers. However

MultiMedVision: Multi-Modal Medical Vision Framework

arXiv:2605.09151v1 Announce Type: new Abstract: Multi-modal medical imaging enables comprehensive diagnostics, yet current foundation models process 2D (e.g. X-ray) and 3D (e.g. CT) data with separate

Multimodal Emotion Recognition via Causal-Diffusion Bridge (Affect-Diff)

arXiv:2605.08252v1 Announce Type: new Abstract: Multimodal emotion recognition on CMU-MOSEI faces an extreme imbalance as Happy accounts for 65.9% of samples while three Ekman categories collectively