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MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars

arXiv:2609.22379v1 Announce Type: new Abstract: High-resolution orbital imagery offers a rich record of the Martian surface, but sparse geological labels limit supervised representation learning. We p

local-aiarxiv-cs-cv

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Mask-Aware Execution for Efficient JEPA Training

DGX agent

arXiv:2609.22674v1 Announce Type: cross Abstract: Joint Embedding Predictive Architectures (JEPAs) are becoming a core representation-learning primitive and a building block for latent world models ac

hardwarearxiv-cs-lg

22 Sept 2026

Tutorials

MaskVLA: Visual Masking Against Trajectory Overfitting of Vision-Language-Action Model

arXiv:2609.23565v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models integrate vision-language understanding with executable robot actions, enabling end-to-end learning for robot contro

tutorialsarxiv-cs-cv

Matched-Input Estimates Differ in Sign Across Architectures: Auditing EEG Foundation Models on Motor Imagery

arXiv:2609.23924v1 Announce Type: new Abstract: Pretrained EEG foundation models are increasingly proposed as general-purpose encoders for brain-computer interfaces, yet recent benchmarks disagree abo

Math2Visual-X: A Modular Framework for Pedagogically Aligned Lower-Primary Math Visuals Generation

arXiv:2609.22647v1 Announce Type: new Abstract: Visual representations can help lower-primary learners understand Math Word Problems, but generating classroom-usable visuals remains difficult. Existin

MCP-GRANITE Benchmark: GRANularity Interface TEsting for MCP-Based LLM Agents

arXiv:2609.24161v1 Announce Type: cross Abstract: As LLM agents increasingly interact with external tools through standardized protocols such as MCP, tool-interface design becomes a critical yet under

MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

arXiv:2606.12916v2 Announce Type: replace-cross Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle

agentsarxiv-cs-cl

ME-Brain-1.0: Memory, Cognition and Action for Evolving Embodied Intelligence

arXiv:2609.24271v1 Announce Type: new Abstract: Current embodied systems largely rely on pretrained capabilities that remain fixed after deployment, limiting their ability to learn from physical inter

local-aiarxiv-cs-ro

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

local-aiarxiv-cs-cv

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectori

Measuring Behavioural Signatures of Large Language Models through Psychometric Profiling

arXiv:2609.22934v1 Announce Type: new Abstract: Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize

safetyarxiv-cs-cl

Measuring the Assistant's Harmlessness Preferences on the User Turn

arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays

local-aiarxiv-cs-cl

Measuring the Checker: Mutation Analysis for GPU-Kernel Benchmark Oracles

arXiv:2609.22220v1 Announce Type: new Abstract: Benchmarks for LLM-generated GPU kernels decide correctness with a few random inputs and a loose floating-point tolerance, and their verdicts now feed l

MECAIL: Communication-Aware Incremental Learning for Object Detection with 14.6 KB Spatiotemporal Experts

arXiv:2609.24455v1 Announce Type: new Abstract: Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However,

Applications

MechaTerp-TRACE: A Novel Approach for Component Ablation Analysis in Language Models

arXiv:2609.22163v1 Announce Type: new Abstract: Interpretability research on large language models has produced accounts of factual recall in feed-forward layers and of token relationships in self-att

applicationsarxiv-cs-cl

MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine

model-releasesarxiv-cs-cl

arXiv:2603.00842v2 Announce Type: replace Abstract: Biomedical multimodal assistants have the potential to unify radiology, pathology, and clinical-text reasoning, yet a critical deployment gap remain

MemCalib: Benchmarking and Optimizing Memory Use in LLM Agents

arXiv:2609.24259v1 Announce Type: new Abstract: The effectiveness of agent memory ultimately depends on whether the underlying LLM gives each memory in context an appropriate degree of influence over

Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization

arXiv:2502.01562v3 Announce Type: replace Abstract: As the general capabilities of artificial intelligence (AI) agents continue to evolve, their ability to learn to master multiple complex tasks throu

Memory That Looks Forward: A Zero-Inference Prospective Term for Personal Memory Retrieval

model-releasesarxiv-cs-cl

arXiv:2609.22091v1 Announce Type: new Abstract: Retrieval over a personal memory store is retrospective: it surfaces what resembles the query, and it is blind to what the user has committed to do. We

Memory vs. Context? Influential Factors of Factual Recall in Language Models

arXiv:2609.24238v1 Announce Type: new Abstract: We reproduce and stress-test the work of Yu et al. (2023), who characterize how language models (LMs) arbitrate between memorized knowledge and contradi

researcharxiv-cs-cl

Merge++: Universal Merge Refinement Through Data-Free Checkpoint Inversion

arXiv:2609.22886v1 Announce Type: new Abstract: Model merging consolidates fine-tuned experts into one multi-task model without retraining. All existing data-free methods approach this problem entirel

Meta patches Muse exploit that let attackers control the AI agent

Meta has issued a patch for its Muse macOS app following the discovery of a zero-day vulnerability that could allow someone to take control of the AI agent. The bug found by security researcher Patric

agentsthe-verge-ai

Tutorials

Metadata Supervised Imaging Representations for Modelling and Controlling Acquisition Variability

arXiv:2607.11295v2 Announce Type: replace Abstract: Biomedical imaging data exhibit substantial acquisition variability, where identical biological structures can appear markedly different due to diff

tutorialsarxiv-cs-cv

MGRD: Compact morphology-gated residual diffusion for variance-aware cross-domain neurite forecasting

arXiv:2609.23990v1 Announce Type: new Abstract: Tracking neurite morphology over time helps characterize structural changes during neuronal development and deterioration, but long-term time-lapse imag

MIGA:Shared-Geometry Gaussian Representation with Implicit Amplitude Modeling for Accelerated 3D Multi-Echo MRI

arXiv:2609.24468v1 Announce Type: new Abstract: Three-dimensional multi-echo MRI provides rich anatomical and quantitative information, but repeated volumetric encoding prolongs acquisition and motiva

MIGU: Multimodal Instruction Grounding under Uncertainty for Manipulation Planning

model-releasesarxiv-cs-ro

arXiv:2609.24995v1 Announce Type: new Abstract: Understanding natural human instructions is crucial for deploying robots in human-centric environments. We study multimodal instruction grounding, where

MimicAgent: Quadruped Skills via Prompt-to-Trajectory Generation

model-releasesarxiv-cs-ro

arXiv:2609.24145v1 Announce Type: new Abstract: We present MimicAgent, a prompt-to-trajectory generation framework for learning dynamic quadruped skills. Although reward shaping is extensively used wh

MiMo-V2.6-Flash on vLLM: fixes for 'empty responses' with thinking + tools, and a hidden 2,048-token output cap

model-releasesr-localllama

Some people here say MiMo-V2.6 is bad with tools and are going back to GLM-5.3-Flash. I spent today running MiMo-V2.6-Flash-RL as the backend for an agent harness, on 2× DGX Spark with vLLM, using the

MiMo-V2.6 is 'simply' the best (for now). Despite its simple architecture design it's currently No.1 in the open-weight benchmarks (weighted…

model-releasessebastian-raschka--x

MiMo-V2.6 is 'simply' the best (for now). Despite its simple architecture design it's currently No.1 in the open-weight benchmarks (weighted average). With 'simple,' I mean a classic Grouped Query Att

MinCU: A Fine-Grained Benchmark for Grounded Minimal-Change Understanding in Image Pairs

arXiv:2609.23336v1 Announce Type: new Abstract: Localizing and describing fine-grained differences between near-identical images is a critical yet underexplored capability for multimodal large languag

Mind or Message? Auditing Theory of Mind in Multi-Agent Social Simulation

arXiv:2609.24146v1 Announce Type: new Abstract: Language model agents are increasingly used to simulate social interaction, and the resulting transcripts read as though the agents understand one anoth

agentsarxiv-cs-lg

Mind the Gaps: A Curated Benchmark for Form Field Detection

arXiv:2609.23679v1 Announce Type: new Abstract: Form Field Detection (FFD) is a fundamental component of document understanding systems, enabling applications ranging from large-scale industrial digit

mini-AGI: Continual-learning dynamically looped transformer with evolutionary grown (on a laptop)

model-releasesr-localllama

Saw this today and found it very intriguing. Lots of interesting design choices here, and it's cool to see someone doing something different. Here's a few highlights: Looped transformer: dynamic recur

Minimum Time Trajectories for a Car-Like Mobile Robot Moving with Rigid Wheels Under Non-Sliding Constraints

arXiv:2609.24832v1 Announce Type: new Abstract: This paper studies the minimum time trajectoriesvof a car-like mobile robot navigating in an obstacle free environment. The robot, with forward and back

researcharxiv-cs-ro

MIRA-PRM: Mission-Informed Reusable Roadmap Planning for Mobile Gas-Sensing Inspection

model-releasesarxiv-cs-ro

arXiv:2609.22954v1 Announce Type: new Abstract: Mobile gas-sensing inspection requires a mobile platform to reliably reach ordered sampling poses. We present MIRA-PRM, a mission-informed probabilistic

MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions

arXiv:2609.24547v1 Announce Type: new Abstract: Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive,

safetyarxiv-cs-ro

Mira-Scene: Pixel-Aligned Layouts for Generative 3D Scene

arXiv:2609.23796v1 Announce Type: new Abstract: Single-image 3D object generation can now produce high-fidelity assets, yet accurately placing them into a coherent scene layout remains an open challen

safetyarxiv-cs-cv

MIRAGE: Full-Body Bystander Privacy for Smart Glasses with Consent-Based Restoration

arXiv:2609.24537v1 Announce Type: new Abstract: Video recording on smart glasses exposes more than faces. Continuous capture reveals full-body biometric signatures, including gait, posture, and silhou

MIS-Bench: Benchmarking Multimodal LLMs for Psychotherapeutic Interpersonal Skills Assessment

model-releasesarxiv-cs-cl

arXiv:2609.22778v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly used as evaluators, yet their reliability in professional assessment tasks that require expert

Misaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models

arXiv:2609.23999v1 Announce Type: new Abstract: How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood. We investigated how four open-weight LLM

MiTHras: Task-specific Hierarchical Semi-supervised Contrastive Masked Autoencoder for Mitotic Figure Analysis

arXiv:2609.24736v1 Announce Type: new Abstract: Mitotic figure (MF) analysis supports tumor grading and prognostic assessment, but automated models remain sensitive to differences in tissue type and i

Mitigating Entity Type Confusion in Cross-Domain NER via Multidimensional Quantification and Reasoning Enhancement

arXiv:2609.24357v1 Announce Type: new Abstract: Cross-domain Named Entity Recognition (CD-NER) aims to transfer the rich knowledge in the source domain to the target domain. Recent studies adopting de

researcharxiv-cs-cl

MixiMotion: One-Step Text-to-Motion Generation via Asymmetric Set Distillation

arXiv:2609.23010v1 Announce Type: new Abstract: Iterative text-to-motion generation delivers high-quality and semantically aligned motions but requires multiple network evaluations, resulting in subst

safetyarxiv-cs-cv

MM-ContextFold: Context Folding for Multimodal Agentic Retrieval

arXiv:2609.23121v1 Announce Type: new Abstract: Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools. Typical frameworks

agentsarxiv-cs-cv

MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments

arXiv:2505.12254v3 Announce Type: replace Abstract: Existing visual place recognition (VPR) datasets predominantly rely on vehicle-mounted imagery, offer limited multimodal diversity, and underreprese

Applications

Mobile Imaging Solutions for Medical Diagnosis: Trends and Applications

arXiv:2609.24814v1 Announce Type: new Abstract: Advances in processing power, camera technologies, and mobile image analysis have made smartphones and other mobile devices, such as laptops, increasing

applicationsarxiv-cs-cv

MobileCybench: Evaluating Agent Vulnerability Discovery via Executable Probes

arXiv:2609.23980v1 Announce Type: cross Abstract: AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application,

Model-Agnostic Feature Selection via LOCO-Guided Adaptive Minipatch Sampling

arXiv:2609.24126v1 Announce Type: cross Abstract: Black-box machine learning models increasingly deliver strong predictions, but extracting useful information from them, such as a set of important fea