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arXiv:2610.05100v1 Announce Type: new Abstract: State-of-the-art neural operators scale to complex meshes via slice-and-process architectures, yet many rely on linear compatibility scores for latent t

tutorialsarxiv-cs-lg

MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation

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arXiv:2610.05252v1 Announce Type: new Abstract: Diffusion-based dataset distillation (DD) suffers from a fundamental objective mismatch: likelihood-driven diffusion models prioritize density approxima

safetyarxiv-cs-cv

6 Oct 2026

Local Ai

Microsoft confirms OpenAI has been using Looped Transformers in the GPT-6 series

Microsoft confirms on publicly accessible web page that OpenAI has been using Looped Transformers in the GPT-6 series, proving The Information's reporting was correct all along. GPT-6.1 Sol uses 2 inf

local-air-localllama

MiMo V2.6 Pro almost matched GPT-6 Astra at figuring out what a user actually wants

model-releasesr-localllama

Introducing InferBench: A benchmark testing how well frontier LLMs infer a user's priorities from their instructions. We tested 12 LLMs across 20 scenarios with 2.8k conversations to see which models

MIND: Microstructure INverse Design with Generative Hybrid Neural Representation

arXiv:2502.02607v2 Announce Type: replace Abstract: The inverse design of microstructures plays a pivotal role in optimizing metamaterials with specific, targeted physical properties. While traditiona

safetyarxiv-cs-cv

Mind the Drift: Diagonal Linear Networks Under Large Learning Rates

arXiv:2610.06120v1 Announce Type: new Abstract: Large learning rates can qualitatively change the trajectory of neural network training, often pushing optimization into regimes far from classical grad

Mind the Execution Gap: Action-Semantic Mismatch in World-Model Control

arXiv:2610.06582v1 Announce Type: cross Abstract: World-model controllers rely on action-conditioned dynamics for prediction and planning, yet real control systems often execute commands asynchronousl

Mind the Gaps: From Failure Attribution to Closed-Form Repair of Code Language Models

arXiv:2610.05277v1 Announce Type: cross Abstract: Code language models must be maintained like the software around them: when a library evolves, a model keeps writing the interface that it saw during

Minority Collective Action for User-Side Fairness

arXiv:2508.15374v3 Announce Type: replace Abstract: Machine learning models often preserve biases present in training data, leading to unfair treatment of certain minority groups. Despite an array of

Tutorials

MIRT: Transformers for Truthful Generative Auctions with Whole-feed Permutation Externalities

arXiv:2610.06559v1 Announce Type: cross Abstract: Modern online platforms commonly rank ads and organic content separately before blending them into a feed displayed to the user, overlooking externali

tutorialsarxiv-cs-lg

Mistral 4 is pretty good at lawyer bench and cyber security bench, but give it's European heritage, one can only assume it's also good at re…

model-releasesdylan-patel--x

Mistral 4 is pretty good at lawyer bench and cyber security bench, but give it's European heritage, one can only assume it's also good at regulation bench Meet Mistral Large 4, aka Le Chonk. • 1T para

Mistral can pelican now! https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F0db8b8196e57711b…

model-releasessimon-willison--x

Mistral can pelican now! https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F0db8b8196e57711b352f6c5857cf5b35#response-1 Meet Mistral Large 4, aka Le Cho

Mistral Large 4

model-releasessimon-willison

My comment on Mistral Large 4 — Hacker News. wren6991: The benchmark is saturated. Frontier models are tested with an armadillo in fishnet tights jaywalking on Mars. OK well I couldn't resist this one

Mistral Large 4 against the field: efficiently reasoning over diverse complex challenges. CTF speedrun: 19 challenges, with tool calls and s…

model-releasesmistral-ai--x

Mistral Large 4 against the field: efficiently reasoning over diverse complex challenges. CTF speedrun: 19 challenges, with tool calls and solve times grounded in actual runs. It solved 18 of the 19.

Mistral Large 4 is one of the world's strongest AI models for cybersecurity.

model-releasesmistral-ai--x

Mistral AI announced that its new model, Mistral Large 4, is among the world's most powerful AI systems specifically designed for cybersecurity tasks. The tweet shared on October 6, 2026 highlights th

Mistral launches a preview of Mistral Large 4, or Le Chonk, a 1T model it claims tops any open model developed in the US or Europe; weights are due October 27 (Carl Franzen/VentureBeat)

Carl Franzen / VentureBeat: Mistral launches a preview of Mistral Large 4, or Le Chonk, a 1T model it claims tops any open model developed in the US or Europe; weights are due October 27 — Mistral is

model-releasestechmeme

Mistral launches open-source Mistral Large 4, details AI roadmap

model-releasessiliconangle

Mistral AI SAS today opened access to Mistral Large 4, its most capable large language model to date. On launch, the LLM is available in public preview through the company’s cloud platform. Mistral pl

Mistral releases Mistral Large 4, dubbed 'le Chonk', a 1T-parameter open-weight model for general agentic capabilities, trained on 4,000 Grace Blackwell GPUs (Sabrina Ortiz/The Deep View)

Sabrina Ortiz / The Deep View: Mistral releases Mistral Large 4, dubbed “le Chonk”, a 1T-parameter open-weight model for general agentic capabilities, trained on 4,000 Grace Blackwell GPUs — Most flag

model-releasestechmeme

Mistral says it trained ML4 'from scratch' using 3,800 Nvidia Grace Blackwell GPUs in its data centers in Europe and much of its training data was multilingual (Mistral Blog)

Mistral Blog: Mistral says it trained ML4 “from scratch” using 3,800 Nvidia Grace Blackwell GPUs in its data centers in Europe and much of its training data was multilingual — Le Chonk — Today, we're

model-releasestechmeme

Mitigating Over-squashing without Rewiring: A Sheaf Effective Resistance Perspective

arXiv:2610.04157v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) often struggle to capture long-range dependencies due to over-squashing -- a phenomenon in which the repeated compression

ML-OPF-Bench: Benchmarking Machine Learning for Optimal Power Flow

model-releasesarxiv-cs-lg

arXiv:2610.04307v1 Announce Type: cross Abstract: Machine Learning (ML) methods promise a fast solution process for Optimal Power Flow (OPF). While inconsistent test cases, implementations, and evalua

MMLongCite: A Benchmark for Evaluating Faithfulness of Long-Context Vision-Language Models

arXiv:2510.13276v2 Announce Type: replace Abstract: The rapid advancement of long-context vision language models (LCVLMs) has led to a significant expansion of their context windows. However, an exten

Mobile-4DGS: Unified Static-Dynamic Real-time Mobile Gaussian Splatting

arXiv:2610.05289v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable performance in novel view synthesis, yet deploying both static and dynamic Gaus

MoCAR: Motion-code Coordinate-aware AutoRegression for Continuous Trajectory Forecasting

arXiv:2610.06210v1 Announce Type: new Abstract: Autoregressive generation is natural for language, where predicted tokens can be directly reused as the next prediction state, but trajectory forecastin

safetyarxiv-cs-cv

model : add K2 Horizon dense and MoVA support by bitalov · Pull Request #29535 · ggml-org/llama.cpp

model-releasesr-localllama

guys do you still remember K2 Horizon? https://huggingface.co/IFM/K2-Horizon-MoVA-36B-A4B-GGUF https://huggingface.co/IFM/K2-Horizon-32B-GGUF https://huggingface.co/IFM/K2-Horizon-3.7B-GGUF https://hu

Modeling Deletion Requests in Machine Unlearning

arXiv:2610.04310v1 Announce Type: new Abstract: Machine unlearning is seen as a promising approach to enable users to exercise the 'right to erasure' in the context of AI models. We ask how users migh

MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation

arXiv:2503.09950v2 Announce Type: replace Abstract: In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans b

applicationsarxiv-cs-cv

Local Ai

Moment-Accurate Gaussian Mixtures for Constant-Step Stochastic Approximation

arXiv:2610.05595v1 Announce Type: cross Abstract: Local Gaussian models of constant-step learning predict output variability and expected losses, but weak convergence alone does not justify these mome

local-aiarxiv-cs-lg

Monitorability Disposition in Large Reasoning Models

arXiv:2610.04914v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of large reasoning models (LRMs) is a common way to detect misbehavior in real-world practice. However, current

Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury

arXiv:2610.05552v1 Announce Type: new Abstract: Three-dimensional gait analysis guides rehabilitation after spinal cord injury but depends on marker-based motion capture and force plates, which few cl

MOSAIC-SV: Real-Time Adaptive Identification of Vessel Dynamics for the Control and Deployment of Aquatic Robots

arXiv:2610.03898v1 Announce Type: new Abstract: Model-based control of an aquatic robotic platform depends on a hydrodynamic model that is costly to identify and specific to the hull, payload, and con

researcharxiv-cs-ro

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based

MOXIE: Discovering Alternative Explanations for Biomedical Image Classifiers

arXiv:2610.04814v1 Announce Type: new Abstract: Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from one fixed image segmentation. This hides t

MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity

arXiv:2610.06378v1 Announce Type: new Abstract: The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video

MTRACE: Multilingual Retrieval-Augmented Generation for Temporally Diverse Text Corpora

arXiv:2512.12694v2 Announce Type: replace-cross Abstract: Large multilingual knowledge bases expose temporally diverse information, yet retrieval quality remains sensitive to lexical variation and cro

Local Ai

MTV: Revisiting Multi-Task Visual Representation Learning

arXiv:2601.13886v2 Announce Type: replace Abstract: Current visual representation learning remains bifurcated: vision-language models (e.g., CLIP) excel at global semantic alignment but lack spatial p

local-aiarxiv-cs-cv

Mulligan: Performance-Guided Data Collection for Efficient On-Robot Learning

arXiv:2610.05882v1 Announce Type: cross Abstract: Learning from human demonstrations is a reliable way to teach robots new tasks, but the gains from each additional demonstration shrink as the policy

Multi-Agent Spectrum Sharing

model-releasesarxiv-cs-lg

arXiv:2610.04802v1 Announce Type: new Abstract: This project explores how multiple cognitive radars can learn to share limited wireless spectrum with other radio users without interfering with one ano

Multi-Crop Leaf Disease Recognition: A Unified Benchmark and Cross-Region Study

arXiv:2610.04456v1 Announce Type: new Abstract: Deep learning models for crop leaf disease recognition routinely report near-perfect accuracy yet are typically trained and evaluated on a single datase

Multi-Marginal Schrodinger Bridge Matching

arXiv:2510.16587v2 Announce Type: replace-cross Abstract: Understanding the continuous evolution of populations from discrete temporal snapshots is a critical research challenge, particularly in field

applicationsarxiv-cs-lg

Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data

arXiv:2610.06389v1 Announce Type: new Abstract: Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context. However, learning both tasks i

MultiLoc: Look Around As You Localize for Fast And Robust Visual Re-localization

arXiv:2603.27170v2 Announce Type: replace Abstract: Relative camera pose is a basic geometric cue for visual re-localization and scene understanding. When using images alone, visual evidence may not s

Multimodal Deep Survival Analysis for Sinkhole Susceptibility

arXiv:2610.06365v1 Announce Type: new Abstract: Sinkholes are a widespread geohazard in karst terrain. In Florida, soluble carbonate bedrock, shallow groundwater, and intense rainfall combine to make

applicationsarxiv-cs-lg

Multitask Conditional Generative Adversarial Network Enables Automatic Whole Knee Cartilage and Menisci Segmentation and Reliable T1r{ho} and T2 Quantification Without High-Resolution Morphological Images

arXiv:2610.06602v1 Announce Type: new Abstract: Early osteoarthritis detection through quantitative MRI (qMRI) requires accurate cartilage and meniscus segmentation, traditionally necessitating time-c

MuViSeg: Multi-View Segment Correspondences from Dense Geometry Priors

arXiv:2607.17938v2 Announce Type: replace Abstract: Object-level mapping and topological navigation reason about whole objects, yet the correspondences they rely on are computed over keypoints or pixe

NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis

arXiv:2610.04722v1 Announce Type: new Abstract: Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, maki

Near-Optimal Complexity of Finite-Sum Nonconvex-Strongly-Concave Minimax Optimization

arXiv:2610.04944v1 Announce Type: cross Abstract: We characterize, up to logarithmic factors, the minimax expected query complexity of finite-sum nonconvex-strongly-concave optimization under mean-squ

NetApp aims to make legacy data AI-ready without a rebuild

Enterprises sitting on decades of legacy information face a pressing question as artificial intelligence moves from pilots to production: Can that archive become AI-ready data without a costly rebuild

applicationssiliconangle