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Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks

arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks becaus

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Hardware

LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models

DGX agent

arXiv:2610.05051v1 Announce Type: new Abstract: Time-series data are often sampled irregularly at high frequencies and exhibit long-range dependencies, which makes long-horizon modelling difficult. Co

hardwarearxiv-cs-lg

6 Oct 2026

Lollypop: Camera-to-Motion-Capture Calibration Verification with a Reference Target

arXiv:2610.04785v1 Announce Type: new Abstract: Camera-to-motion-capture (mocap) calibration is essential for using mocap as ground truth in robotics, AR/VR, and other computer vision tasks. However,

Long-MDR: Long-Context Reinforcement Learning for Multimodal Deep-Research Agents

arXiv:2610.05195v1 Announce Type: new Abstract: The next generation of multimodal research agents must reason over long-lived research histories rather than short model completions. During a single ta

Local Ai

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

arXiv:2610.05023v1 Announce Type: new Abstract: We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image r

local-aiarxiv-cs-cv

LoopMoEVR: Loop-Based Degradation-Aware Mixture-of-Experts for Unified UHD Video Restoration

arXiv:2610.05109v1 Announce Type: new Abstract: Recently, unified high-definition image restoration has attracted considerable attention; however, existing models tend to excessively increase their de

Loopy: Low-Bit Quantization Framework for Looped Language Models

arXiv:2610.05265v1 Announce Type: new Abstract: Looped language models provide a parameter-efficient way to scale iterative test-time computation by repeatedly executing a shared recurrent core. Post-

LoRA Direction Extraction for Controllable Light Toggling in FLUX.1 Kontext

arXiv:2610.03771v1 Announce Type: new Abstract: We propose a fine-tuning method for flow-matching diffusion models aimed at realistic artificial light modeling without the need for a large training da

LoRA's Second Descent Extends Beyond Parameter Parity

arXiv:2610.04507v1 Announce Type: new Abstract: Double descent has sparked considerable interest, with recent work relating it to the data, the model and the learning configuration. Practical fine-tun

Loss-Invariant Projections as Passive Probes of Learned Representations

arXiv:2610.06195v1 Announce Type: cross Abstract: Learned feature representations in neural networks often contain structure beyond that directly used by the final task output. We study this structure

Lossy Compression of PDE Training Inputs: Field Reconstruction Error Does Not Order the Cost to a Trained Operator

arXiv:2610.06095v1 Announce Type: new Abstract: Operator-learning benchmarks are stored at full precision and have grown to terabyte scale. Rate-distortion theory says how many bits the stored field n

Low-Fidelity FDM Spectral Guidance for Neural Eigenvalue Solvers

arXiv:2610.04695v1 Announce Type: new Abstract: Operator eigenvalue problems appear throughout science. Classical methods usually discretize the operator into a matrix and then solve the resulting mat

LyapuFlow: Controlling Generative Flows with Lyapunov Feedback for Inverse Problems

arXiv:2610.04326v1 Announce Type: new Abstract: Pretrained flow models are now widely used as generative priors in science and vision, where inference-time guidance enables test-time constraints witho

M^2-Occ: Resilient 3D Semantic Occupancy Prediction for Autonomous Driving with Incomplete Camera Inputs

arXiv:2603.09737v2 Announce Type: replace Abstract: Semantic occupancy prediction enables dense 3D geometric and semantic understanding for autonomous driving. However, existing camera-based approache

Machine learning for journal entry testing: A type-aware evaluation of anomaly detectors under a review budget

arXiv:2610.06133v1 Announce Type: new Abstract: Journal entry anomaly detectors are commonly evaluated on the full population with ROC-AUC, precision and recall, ignoring the review budget and which a

Machine learning modeling of hit-into-play probability and quantification of pitch sequence effects

arXiv:2606.17345v2 Announce Type: replace Abstract: Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on improving predictive performance for

MaDeL: Manifold-Decomposed Feature Losses for Generative Modeling

arXiv:2610.04419v1 Announce Type: new Abstract: Generative models are often trained with isotropic objectives such as mean-squared error. For data concentrated near a low-dimensional manifold, however

MAGEFormer: Learning Metric-Consistent Representations for Anisotropic CT Segmentation

arXiv:2610.04036v1 Announce Type: new Abstract: Vision Transformers (ViTs) have shown strong performance in volumetric segmentation, but their effectiveness on clinical CT is limited by an isotropic E

MagiC: Evaluating Multimodal Cognition Toward Grounded Visual Reasoning

arXiv:2507.07297v2 Announce Type: replace Abstract: Recent advances in large vision-language models have led to impressive performance in visual question answering and multimodal reasoning. However, i

MAGIC: Topology-Aware Analytic Graph Few-Shot Class-Incremental Learning

arXiv:2610.04963v1 Announce Type: new Abstract: Graph few-shot class-incremental learning (GFSCIL) requires a model to continually recognize emerging classes from only a few labeled nodes while preser

MagServo: Uncertainty-Resilient Hierarchical Magnetic Servoing via Learned Latent Representations

arXiv:2610.06046v1 Announce Type: new Abstract: Magnetic navigation provides contact-free and line-of-sight-independent feedback for robotic systems, yet existing approaches typically rely on explicit

researcharxiv-cs-ro

Malware reverse-engineering: solving an out-of-distribution investigation task. When faced with an unknown binary, Mistral Large 4 reverse-e…

model-releasesmistral-ai--x

Malware reverse-engineering: solving an out-of-distribution investigation task. When faced with an unknown binary, Mistral Large 4 reverse-engineers it end-to-end. In this case, it concludes the sampl

MambaVF: State Space Model for Efficient Video Fusion

arXiv:2602.06017v2 Announce Type: replace Abstract: Video fusion aims to integrate complementary information from multiple source videos while preserving temporal consistency. Effective modeling of te

Industry

Manage Amazon SageMaker HyperPod Spaces directly from SageMaker Studio

Data scientists and ML engineers can now create, configure, start, stop, and open Amazon SageMaker Spaces on SageMaker HyperPod EKS clusters directly from SageMaker Studio. Launch JupyterLab and Code

industryaws-ml-blog

Agents

Managed Apache Iceberg at scale: How Spanner powers Lakehouse runtime catalog

As customers modernize to lakehouse architectures, they are standardizing on open formats such as Apache Iceberg to create a shared data estate across compatible engines. This enables you to build AI-

agentsgoogle-cloud-ai

ManifoldCache: Training-Free Diffusion Acceleration via Constraint Manifold Caching

arXiv:2610.04510v1 Announce Type: cross Abstract: Diffusion models for structured scientific generation must produce samples satisfying hard geometric constraints imposed by physics, chemistry, or bio

Mapping and Classification of Trees Outside Forests using Deep Learning

arXiv:2510.25239v2 Announce Type: replace Abstract: Trees Outside Forests (TOF) play an important role in agricultural landscapes by supporting biodiversity, sequestering carbon, and regulating microc

MaRO-GS: Mask-Robust Object-Centric Gaussian Splatting from Inconsistent Multi-view Masks

arXiv:2610.06472v1 Announce Type: new Abstract: We address the challenge of accurate 3D object reconstruction from multi-view images in Gaussian Splatting. Existing object-level 3DGS methods reconstru

MarvisNav: Making Memory Visible on Route Choices for Zero-Shot Object Navigation

arXiv:2610.06510v1 Announce Type: new Abstract: When searching for an object, people choose their next move by considering both likely target locations and places already explored. The current view ca

safetyarxiv-cs-ro

Masked Privileged-Information Distillation for Multimodal Skin Lesion Classification Under Missing Clinical Metadata

arXiv:2610.03991v1 Announce Type: new Abstract: Multimodal skin lesion classification combines clinical images with patient metadata to improve diagnostic accuracy. However, complete metadata availabl

MatrixFormer: A Foundation Model for Matrix Completion

arXiv:2610.06751v1 Announce Type: new Abstract: Matrix completion underlies problems from tabular imputation to causal inference, yet existing tabular foundation models treat it as entry-by-entry pred

Hardware

MC-Sparse: Deconstructing and Closing the Dense-Sparse Attention Gap in Diffusion Transformers

arXiv:2610.06801v1 Announce Type: new Abstract: Sparse attention is a primary approach to reducing the latency of diffusion transformers in long-sequence generation tasks, such as video and high-resol

hardwarearxiv-cs-cv

MDKeyChunker: What Does One LLM Call per Chunk Buy for Markdown Retrieval?

arXiv:2603.23533v3 Announce Type: replace-cross Abstract: Markdown carries structure a parser reads for free: headers, section paths, and block boundaries. Many RAG pipelines also spend LLM calls per

Hardware

Measuring and Reducing Cross-Vendor Mismatch in Language Models

arXiv:2610.05458v1 Announce Type: new Abstract: Running the same language model on different graphics processing unit (GPU) vendors can produce different logits, even when the model weights and inputs

hardwarearxiv-cs-lg

Measuring Effective Data Resolution in Guided Diffusion Posteriors

arXiv:2610.04422v1 Announce Type: new Abstract: Guided diffusion samplers are increasingly used to reconstruct physical fields from sparse observations, but standard diagnostics do not say how much of

Measuring Learned Monotone Temporal Aggregation at Matched Admissibility

arXiv:2610.05196v1 Announce Type: new Abstract: Risk regulation imposes directional constraints on scores; we adopt their strict per-input form -- the score monotone non-decreasing in every exposure i

MedAD-R1: Consistency-Reinforced Policy Optimization for Interpretable Medical Anomaly Detection

arXiv:2602.01081v2 Announce Type: replace Abstract: Medical Anomaly Detection (MedAD) offers a promising direction for medical image analysis with Large Multimodal Models (LMMs). However, progress is

MedImageOSWorld: Benchmarking GUI Agents for Medical Image Consoles

arXiv:2610.04800v1 Announce Type: cross Abstract: Graphical consoles offer a practical interface for medical acquisition assistance, allowing agents to work through the controls and visual feedback us

Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on…

model-releasesclem-delangue--x

Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workl

MemLeak: Cross-User Semantic Leakage in Multi-Tenant AI Agent Memory

arXiv:2610.04195v1 Announce Type: cross Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface f

Memoria 1.0.0 — a local, model-agnostic memory system for LLMs

model-releasesr-localllama

I’ve been building this for a long fucking time, and tonight I finally released Memoria 1.0.0. I built it because I actually wanted to use it. I wanted a real memory layer for local LLM applications t

Memory-State Critic for Asymmetric Actor-Critic with Application to Vision-Based Pursuit-Evasion

arXiv:2610.03830v1 Announce Type: new Abstract: In partially observable Markov decision processes, the optimal policy generally depends on the history of observations and past actions. Asymmetric acto

safetyarxiv-cs-lg

MemPilot: Orchestrating On-Demand Multimodal Memory Curation for LLM Agents

arXiv:2610.06830v1 Announce Type: cross Abstract: Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent me

safetyarxiv-cs-lg

MEND: RL For Flow Models via Proximal Velocity Matching

arXiv:2610.05954v1 Announce Type: cross Abstract: Reward post-training of flow models either reweights the model's own samples under a KL penalty or a frozen reference, often for thousands of updates,

Local Ai

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

local-aiarxiv-cs-lg

MeSD: Multi-Evidence Self-Distillation for VideoLLM

arXiv:2610.06342v1 Announce Type: new Abstract: While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-lev

Agents

Meta, Walmart, Instinct, Shopify, Sierra, Stripe, and others publish the Personal Agent Protocol to standardize and secure how AI bots interact with businesses (Kate Rooney/CNBC)

Kate Rooney / CNBC: Meta, Walmart, Instinct, Shopify, Sierra, Stripe, and others publish the Personal Agent Protocol to standardize and secure how AI bots interact with businesses — A month after Meta

agentstechmeme

Hardware

MetaKernelBench: Measuring GPU Kernel Knowledge Transfer Beyond Code

arXiv:2610.05014v1 Announce Type: new Abstract: Recent GPU kernel optimization agents retain what they learn in knowledge bases or as distilled skills. Kernel benchmarks score each attempt's implement

hardwarearxiv-cs-lg