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M3SunAgent: Monocular 3D Spatial Understanding Agent for Metric Depth Estimation and 3D Visual Grounding

model-releasesarxiv-cs-cv

arXiv:2610.07982v1 Announce Type: new Abstract: Monocular metric depth estimation and 3D visual grounding represent the two complementary cornerstones of monocular 3D spatial understanding (M3Sun), fr

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Machine Learning for German Redispatch Forecasting under Data Delays and Temporal Distribution Shift

DGX agent

arXiv:2610.08337v1 Announce Type: cross Abstract: Public redispatch records provide empirical data for grid congestion forecasting, but delayed reporting, zero-inflated distributions, and temporal shi

model-releasesarxiv-cs-lg

7 Oct 2026

Machine learning Majorana topology using unsupervised and supervised learning

model-releasesarxiv-cs-lg

arXiv:2512.13825v2 Announce Type: replace-cross Abstract: In unsupervised learning, the training data for deep learning does not come with any labels, thus forcing the algorithm to discover hidden pat

Local Ai

MacJEPA: Missingness-Robust Audio-Visual Recognition from Untrimmed Egocentric Videos

arXiv:2610.08192v1 Announce Type: new Abstract: Audio-visual models improve egocentric action recognition by exploiting complementary cues, yet typically assume that both streams remain available at i

local-aiarxiv-cs-cv

Magnet-Aware Control of Legged Robots

arXiv:2610.08653v1 Announce Type: new Abstract: Autonomous robots can increase uptime and reduce human exposure in Big Science facilities, but strong magnetic fields needed for their operation corrupt

agentsarxiv-cs-ro

Making COMET Comparable Across Scripts: Diagnosis and Correction of Tokeniser-Induced Script Bias in Indic MT Evaluation

arXiv:2610.08159v1 Announce Type: new Abstract: COMET reports translation quality as a single number, and that number is routinely compared across target languages written in different scripts. Such a

safetyarxiv-cs-cl

managed deep agents 0.9 is here! things we shipped: ⏰ agents can schedule tasks OBO themselves or the user 🏭 dynamically configure your mda…

model-releasesharrison-chase--x

managed deep agents 0.9 is here! things we shipped: ⏰ agents can schedule tasks OBO themselves or the user 🏭 dynamically configure your mda per run (models, tools, skills, etc.) 👀 Slack reactions show

MARCO: The Radioactive Watermark for Protein Generative Models

arXiv:2610.08316v1 Announce Type: cross Abstract: Protein Generative Models (PGMs) have revolutionized structural biology by enabling the design of complex 3D protein structures from sequence data. Ho

MARS: Multi-resolution Adaptive Routing for Sequential Recommendation

arXiv:2610.07505v1 Announce Type: new Abstract: Long-history recommenders often compress each user's history into a compact, candidate-independent memory that is cached and reused to score large candi

MASC: A Multi-Agent Self-Calibration Framework with Latent Construct Alignment for Consistent Client Role-Playing in Psychological Counseling

arXiv:2610.08250v1 Announce Type: new Abstract: Large language models are increasingly used to simulate clients for counselor training and psychological counseling research, but reliable simulation re

Tutorials

Mask-Guided KV Cache Eviction in Block Diffusion Language Models

arXiv:2610.06996v1 Announce Type: cross Abstract: Block diffusion language models keep a large key-value (KV) cache throughout generation and attend to it at every denoising step, limiting both memory

tutorialsarxiv-cs-ai

MASKerade: Token-Routed Mask Experts for Dense-to-MoE Upcycling

model-releasesarxiv-cs-lg

arXiv:2610.07809v1 Announce Type: new Abstract: Sparsely activated Mixture-of-Experts (MoE) models increase model capacity without a proportional increase in per-token computation. Dense-to-MoE upcycl

Massive Activation Gating Channel in Large Language Models

arXiv:2610.07661v1 Announce Type: new Abstract: Massive activations, a phenomenon in which a small number of hidden channels exhibit exceptionally large magnitudes, are pervasive in large language mod

Matching Object or Relation? Tracing Abstract Reasoning Inside VLMs

arXiv:2610.07646v1 Announce Type: new Abstract: Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document thi

Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction

arXiv:2610.07712v1 Announce Type: cross Abstract: Existing molecular and materials learning approaches often rely on a limited set of structural representations, which may capture only selected aspect

researcharxiv-cs-lg

Tutorials

Mathematical Proof Assistants for Teaching Logic: The LogiKEy Methodology

arXiv:2610.08214v1 Announce Type: new Abstract: We report on an approach to teaching logic to mixed groups of computer science, mathematics, and philosophy students, based on the logico-pluralistic Lo

tutorialsarxiv-cs-ai

Measuring climate backlash in Twitter and Reddit archives: Lexical definitions, recorded responses and participant turnover

arXiv:2610.07634v1 Announce Type: new Abstract: Social media archives are often used to study resistance to climate action, but words, response counters and observed participants do not measure the sa

Mechanistic Interpretability of Atmospheric Rivers in GraphCast

arXiv:2610.07583v1 Announce Type: cross Abstract: While AI weather models now rival operational forecasts, how they represent the atmosphere internally remains an open question: feature attribution re

Hardware

Mecka, which collects human motion data to train humanoid robots, raised a $60M Series B led by Sequoia, with participation from Nvidia, M12, and others (Marina Temkin/TechCrunch)

Marina Temkin / TechCrunch: Mecka, which collects human motion data to train humanoid robots, raised a $60M Series B led by Sequoia, with participation from Nvidia, M12, and others — Mecka AI, a start

hardwaretechmeme

MedCORE: Criteria-Grounded Clinical Reasoning for Interpretable Medical Image Diagnosis

arXiv:2610.08528v1 Announce Type: cross Abstract: Clinical diagnosis is inherently a structured reasoning process, yet existing deep learning models often bypass this structure by mapping image featur

MedHorizon: Towards Long-context Medical Video Understanding in the Wild

model-releasesarxiv-cs-cv

arXiv:2605.06537v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires

Medical Image Alignment Assessment as a Test of Generalist Visual Reasoning in Frontier Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2610.06896v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) are increasingly positioned as general purpose visual reasoners as part of the quest for artificial ge

MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation

arXiv:2610.08327v1 Announce Type: new Abstract: Large language models (LLMs) have shown promise in medical question answering and clinical reasoning, yet their improvement remains constrained by stati

MemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments

arXiv:2610.07376v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in interactive environments, where they need to make sequential decisions through observation, ac

agentsarxiv-cs-ai

MemFLoRA: Memory-Floor LoRA for CNN Adaptation at the Edge

arXiv:2610.08669v1 Announce Type: cross Abstract: On-device learning is necessary when the model encounters user-,sensor-, or environment-specific shifts after deployment. Although parameter-efficient

MemMux: Runtime Verification and Honest Resource Attribution for Fleets of Parallel Coding Agents

arXiv:2610.07257v1 Announce Type: new Abstract: Developers increasingly run a fleet of coding agents side by side on one workstation. The tools they reach for, terminal multiplexers like tmux and a ne

Applications

Memory Depth and Reconstructed Context Width: A Controlled Evaluation of Hierarchical Retrieval

arXiv:2610.08300v1 Announce Type: new Abstract: Long-term conversational memory is becoming an integral component of modern LLM systems. Proposed architectures group records by topics and events, cons

applicationsarxiv-cs-cl

Local Ai

Memory-Efficient Expert Routing for Distributed MoE Training

arXiv:2610.07333v1 Announce Type: cross Abstract: As Mixture-of-Experts (MoE) models scale toward hundreds of experts and higher top-k routing, memory efficiency in distributed training becomes a crit

local-aiarxiv-cs-ai

Memory Prediction Excess: A Probabilistic Quantity for Predictive Gain and Memory Length in Stochastic Processes

arXiv:2610.06894v1 Announce Type: cross Abstract: A central question in the prediction of stochastic processes is the extent to which past information can improve the probability of correctly predicti

researcharxiv-cs-lg

Applications

Meta, Google DeepMind, and Isomorphic Labs invest 300M and the US invests 500M+ in Zuckerberg-backed Biohub to build open biology datasets for AI training (Krystal Hu/Reuters)

Krystal Hu / Reuters: Meta, Google DeepMind, and Isomorphic Labs invest 300M and the US invests 500M+ in Zuckerberg-backed Biohub to build open biology datasets for AI training — The US government and

applicationstechmeme

Meta teams up with Bret Taylor’s Sierra Technologies on new standards for AI agent commerce

Meta Platforms Inc. is partnering with Walmart Inc., Stripe Inc. and the enterprise artificial intelligence firm Sierra Technologies Inc. on the creation of new standards that will define how autonomo

agentssiliconangle

Tutorials

MetaLearnNCA: Few-Shot Offline Meta-Learning via Interacting Neural Cellular Automata

arXiv:2610.08479v1 Announce Type: cross Abstract: Few-shot meta-learning traditionally formulates task adaptation either as analytical gradient descent through unrolled computational graphs or as metr

tutorialsarxiv-cs-ai

Metonymic Circuits for Abstract Concept Grounding in Vision Transformers

arXiv:2610.06928v1 Announce Type: new Abstract: We study how Vision Transformers ground abstract concepts (e.g., angry) when training data provide limited direct referential evidence. We hypothesize a

Micro Neural Policies for Safe Real-Time Robotic Control

arXiv:2610.08541v1 Announce Type: cross Abstract: In this paper, we investigate the synthesis of Micro Neural Policies (MNP) to enable safe and robust real-time robotic control on computationally cons

safetyarxiv-cs-ai

Local Ai

Microsoft opens preorders for the $5,999 Surface RTX Spark Dev Box, with 128GB of unified memory to run local models with 120B+ parameters, shipping in November (Stevie Bonifield/The Verge)

Stevie Bonifield / The Verge: Microsoft opens preorders for the $5,999 Surface RTX Spark Dev Box, with 128GB of unified memory to run local models with 120B+ parameters, shipping in November — Microso

local-aitechmeme

Midwest Wheel builds toward AI agents that fix problems

Agentic AI governance helps midsized distributors decide which tasks software agents can handle and which require human oversight. For lean IT teams, automating more work also means checking the data

agentssiliconangle

Applications

MIM-VLA: Learning Physical Interaction Representations from Gripper Motor Feedback

arXiv:2610.08425v1 Announce Type: new Abstract: Vision-language-action (VLA) policies infer grasp actions primarily from visual observations and robot state, but do not explicitly represent the physic

applicationsarxiv-cs-ro

MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

arXiv:2610.08586v1 Announce Type: new Abstract: Long conversational agents have become essential in our daily lives. They must remember what was said long back in order to help us efficiently complete

Minimal Witness Reinforcement Learning

arXiv:2610.07226v1 Announce Type: cross Abstract: ``What are the irreducible conditions that are sufficient to produce an outcome?'' is one of the most common questions that recur across computation a

safetyarxiv-cs-ai

MiniScope: Authorizing Agents with Least-Privilege Permissions

arXiv:2512.11147v2 Announce Type: replace-cross Abstract: AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a

Mission-Aware Attestation Envelopes for Time-Critical Autonomous Action: A Hardware-in-the-Loop V2I Study

model-releasesarxiv-cs-ro

arXiv:2610.08771v1 Announce Type: cross Abstract: An autonomous system that asks for a privileged physical action is usually gated on integrity evidence: a platform proves what it is running, and the

Mistral Large 4 runs general-purpose agents that gather information and produce finished deliverables across complex workflows.

model-releasesmistral-ai--x

Mistral AI introduced **Mistral Large 4** in October 2026 as a general‑purpose agentic model capable of gathering information and producing final deliverables across complex workflows. The launch high

Mitigating Concept Drift in QoS Prediction for Teleoperation of Autonomous Vehicles Using Historic Data

arXiv:2610.08297v1 Announce Type: cross Abstract: Teleoperation serves as the fallback solution to autonomous driving but reliable functions of the teleoperation require a certain amount of mobile net

agentsarxiv-cs-ai

MobileVISTA: Generative Data Augmentation for Pose Generalization in Mobile Manipulation

arXiv:2610.07511v1 Announce Type: cross Abstract: Mobile manipulators such as humanoid robots are increasingly deployed in dynamic, unstructured environments to perform dexterous manipulation tasks. H

researcharxiv-cs-cv

Model-Based Geometry-Aware Generative Optimization for Constrained Locomotion Planning

arXiv:2610.07772v1 Announce Type: new Abstract: Constrained Locomotion Planning (CLP) for quadrupeds and humanoids, where robots must satisfy collision avoidance, contact consistency, kinematic feasib

researcharxiv-cs-ro

Modeling Latent Disturbances for Robust Decision-Making in World Models

arXiv:2610.07599v1 Announce Type: cross Abstract: In this paper, we study robust decision-making in the latent space of world models (WMs). Robust optimization is a mathematical framework where, given

safetyarxiv-cs-ai

Modeling Time-Dependent Responses of Optical Compressors with Selective State Space Models

arXiv:2408.12549v4 Announce Type: replace-cross Abstract: This paper presents a method for modeling optical dynamic range compressors using deep neural networks with Selective State Space models. The

MoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization

arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse