All entries

Monitoring Post-Disaster Urban Recovery Using High-Resolution SAR Time Series and Unsupervised Learning: Evidence from the 2023 Turkiye-Syria Earthquake

arXiv:2607.24180v1 Announce Type: cross Abstract: Monitoring post-disaster recovery is essential for understanding how urban systems rebuild and progressively return to functionality. However, trackin

Safety

Moral Hazard in Multi-Agent Language Models

DGX agent

arXiv:2607.23982v1 Announce Type: cross Abstract: Cooperation can fail when socially valuable effort is costly, weakly observable, and mainly benefits others. Drawing on Holmstrom's team moral-hazard

safetyarxiv-cs-ai

28 Jul 2026

Moving-Horizon Estimation and Nonlinear Model Predictive Control of Cable-Driven Soft Manipulators

arXiv:2607.24029v1 Announce Type: new Abstract: Precise control of soft manipulators remains challenging due to the difficulty of developing accurate yet computationally tractable models for model-bas

researcharxiv-cs-ro

MPR-CiteG: Enhancing RAG with Multi-Portfolio Retrieval and Citation-Grounded Generation

arXiv:2607.22706v1 Announce Type: new Abstract: This paper presents the MPR-CiteG framework, which achieved second place in the ScienceON AI Challenge by addressing two fundamental challenges in gener

MS-GPT: Rethinking MS/MS De Novo Structure Elucidation as Spectrum-Induced Posterior Querying of a Molecule-Language Model

arXiv:2607.23607v1 Announce Type: cross Abstract: Molecular structure elucidation from tandem mass spectra (MS/MS) is a central inverse problem in analytical chemistry. Most existing approaches to MS/

safetyarxiv-cs-cl

Applications

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization

arXiv:2512.03522v3 Announce Type: replace-cross Abstract: Robots are often required to localize in environments with unknown object classes and semantic ambiguity. However, when performing global loca

applicationsarxiv-cs-cv

MSVS-VAE: Multi-Scale Anchored VecSet for High-Fidelity 3D Reconstruction

arXiv:2607.24436v1 Announce Type: new Abstract: High-fidelity 3D generative modeling increasingly relies on the latent diffusion paradigm, where the reconstruction quality of the underlying 3D VAE bec

researcharxiv-cs-cv

MulRobBench: A Decision-Level Benchmark for Safe and Security-Policy-Compliant Multimodal UAV Agents

arXiv:2607.23870v1 Announce Type: cross Abstract: Smart-city airspace is transforming Uncrewed Aerial Vehicles (UAVs) from passive sensing platforms into cyber-physical decision makers that must follo

Agents

Multi-agent DRL-based Lane Change Decision Model for Cooperative Platooning in Mixed Traffic

arXiv:2601.11809v2 Announce Type: replace Abstract: Connected automated vehicles (CAVs) possess the ability to communicate and coordinate with one another, enabling cooperative platooning that enhance

agentsarxiv-cs-ai

Agents

Multi-Agent Privacy Game in Federated Learning: A Unified Mean-Field View

arXiv:2607.23029v1 Announce Type: cross Abstract: Federated learning enables collaborative model training across distributed clients without centralising their data, yet privacy remains a persistent c

agentsarxiv-cs-ai

Multi-dimensional training-priority weighting based on physical information propagation paths: a unified residual-weighting framework for physics-informed neural networks

model-releasesarxiv-cs-lg

arXiv:2607.11094v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations (PDEs); however, their synchronous optimizati

Multi-Domain Physics-Based MDO of Multirotor UAVs: A Deterministic Framework for Discrete COTS Sizing

model-releasesarxiv-cs-ro

arXiv:2607.22768v1 Announce Type: cross Abstract: Multirotor Unmanned Aerial Vehicle (UAV) design is governed by a tightly coupled system of non-linear equations spanning structural mechanics, electro

Multi-Modal Object Re-Identification with Prompt-S6 and Semantic-Aware Knowledge Guidance

arXiv:2607.23451v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve specific objects by integrating complementary information from multiple modalities. However

safetyarxiv-cs-cv

Multi-Modal Scene Graph with Kolmogorov-Arnold Experts for Audio-Visual Question Answering

arXiv:2511.23304v2 Announce Type: replace Abstract: In this paper, we propose a novel Multi-Modal Scene Graph with Kolmogorov-Arnold Expert Network for Audio-Visual Question Answering (SHRIKE). The ta

Multi-model approach for autonomous driving: A comprehensive study on traffic sign-, vehicle- and lane detection and behavioral cloning

arXiv:2603.09255v2 Announce Type: replace-cross Abstract: Deep learning and computer vision techniques have become increasingly important in the development of self-driving cars. These techniques play

Multi-Objective Structured Pruning of LLMs for Latency and Model Size Optimization

arXiv:2607.22583v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved widespread adoption because of their strong reasoning and query-response capabilities. However, deploying the

Hardware

Multi-primitive in-memory computing for Monte Carlo tree search

arXiv:2607.22869v1 Announce Type: cross Abstract: Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge d

hardwarearxiv-cs-ai

Multi-Task GRPO: Reliable LLM Reasoning Across Tasks

arXiv:2602.05547v2 Announce Type: replace-cross Abstract: RL-based post-training with GRPO is widely used to improve large language models on individual reasoning tasks. However, real-world deployment

Multimodal Domain Generalization for Depression Detection: An Attention-Based BiLSTM Network with Domain-Adversarial Training

arXiv:2607.22794v1 Announce Type: cross Abstract: Automatic depression detection with deep learning has shown promise but often suffers from limited generalization due to domain shift arising from int

Tutorials

Multimodal Semantic-Probabilistic Objectness for Open World Object Detection

arXiv:2607.23981v1 Announce Type: cross Abstract: Open-world object detection (OWOD) requires a detector to recognize known categories, discover unnamed objects from unseen categories, and incremental

tutorialsarxiv-cs-ai

Multimodal Surface EMG Hand Gesture Recognition Using Query-Based Transformers for Prosthetic Control

arXiv:2607.22779v1 Announce Type: cross Abstract: Hand gesture recognition via surface electromyography (sEMG) is fundamental to prosthetic control. In this field, deep learning approaches have become

local-aiarxiv-cs-ai

Multivariate Time Series Forecasting with Adaptive Non-Local Observables

arXiv:2607.24399v1 Announce Type: cross Abstract: Multivariate time series forecasting (MTSF) predicts future values of multiple variables from historical data. While quantum neural networks have been

local-aiarxiv-cs-ai

Multiview Multi-Person Human Mesh Recovery Under Large Scenes with Occlusions

model-releasesarxiv-cs-cv

arXiv:2607.24302v1 Announce Type: new Abstract: Human mesh recovery (HMR) aims to recover 3D human meshes from images. Most existing HMR benchmarks and methods focus on either multi-person reconstruct

Applications

Music-Source-Separation-Training (MSST): A Unified Framework for Training and Evaluating Music Demixing Models

arXiv:2607.23395v1 Announce Type: cross Abstract: Music Source Separation (MSS), the task of recovering individual sound components (stems) from a polyphonic mixture, is central to applications rangin

applicationsarxiv-cs-lg

Mutual Modality Trust with Lightweight Reconstruction Regularization for Fine-grained Tire Pattern Recognition

arXiv:2607.23979v1 Announce Type: new Abstract: Visual tire recognition serves as a core supporting technique for vehicle safety monitoring, autonomous driving perception and automated automotive main

safetyarxiv-cs-cv

Agents

Mwando: Leveraging AI to Preserve and Teach shiKomori

arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros

agentsarxiv-cs-cl

MXAttention: Data-Free Optimal Scaling and Pre-Normalization Quantization for MXFP4 Attention

arXiv:2607.24377v1 Announce Type: cross Abstract: The quadratic cost of attention is a major bottleneck in diffusion-based video generation models. MXFP4 attention provides a promising path toward eff

My first longer Wan2.2 continuation generation. I am so excited

local-air-stablediffusion

Hey guys, I am so excited to share this with you guys. I know for a lot of Pros here, this maybe a baby's work so please be gentle. Until a month ago, I didnt know anything but to use those google AI

Myopia Prevention and Control 3.0: Artificial Intelligence--Driven Risk Stratification, Proactive Monitoring, and Personalized Intervention

arXiv:2607.24187v1 Announce Type: new Abstract: The convergence of artificial intelligence (AI), digital sensing, and ubiquitous computing has created an unprecedented opportunity to transform myopia

N_0-TWAM: Scaling Tactile-Native World-Action Model for Contact-Rich Manipulation

arXiv:2607.23783v1 Announce Type: new Abstract: We present N_0-TWAM, a tactile-native world-action model for contact-rich manipulation that predicts both future vision and future contact. To our knowl

researcharxiv-cs-ro

N_0-VTLA: Scaling Vision-Tactile-Language-Action Model with Latent Tactile Tokens

arXiv:2607.23782v1 Announce Type: new Abstract: We present N_0-VTLA, a vision-tactile-language-action (VTLA) foundation model capable of (1) fine-grained contact-rich manipulation with tactile percept

safetyarxiv-cs-ro

Industry

N00b installed ChatGPT MacOS - Help me to not default to codex

I installed for the first time chatgpt on macos, downloaded the file form OpenAI. Everytime i open the chatgpt 'prompt' it defaults to 'Codex' as i am doing some kind of project or work? i just want t

industryr-chatgpt

Nearly Tight Bounds for Cross-Learning Contextual Bandits with Graphical Feedback

arXiv:2502.04678v2 Announce Type: replace Abstract: Repeated first-price auctions are contextual decision problems with censored but reusable feedback: after submitting a bid, a learner can infer the

NEO: NeRF It Once, Edit It Many Times for Continuous Object Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.24538v1 Announce Type: new Abstract: In this paper, we present NEO, a unified framework providing language-guided NeRF editing for robotic manipulation. Our paper introduces (i) a language-

Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder

arXiv:2607.23554v1 Announce Type: cross Abstract: In this paper, we propose the MAEConformer, a novel self-supervised learning framework that combines the Conformer architecture with the Masked Autoen

local-aiarxiv-cs-ai

Neptuna: A Comprehensive Machine Learning Framework for Benchmarking Complex Multiphase Flows

arXiv:2607.22280v2 Announce Type: replace-cross Abstract: Compressible multiphase flows involving shocks and material interfaces arise in applications such as bubble collapse and droplet breakup, wher

Nesterov acceleration in optimizing over probability measures

arXiv:2607.23008v1 Announce Type: cross Abstract: Optimization over probability measures has become an increasingly important paradigm in modern machine learning, scientific computing, and uncertainty

Hardware

netflix’s stack

hardwareyohei-nakajima--x

netflix’s stack In-House LLM Serving at Netflix Netflix built an in-house LLM serving platform using vLLM and NVIDIA Triton, integrating self-hosted models into its existing production infrastructure

Neural Dynamics of AI-attributed Irony Reveal a Partial Intentional Stance

arXiv:2510.17168v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly deployed as social agents and trained to produce humor and irony, a question emerges: when encounte

researcharxiv-cs-cl

Neural Message-Passing on Attention Graphs for Hallucination Detection

arXiv:2509.24770v2 Announce Type: replace Abstract: Large Language Models (LLMs) often generate incorrect or unsupported content, known as hallucinations. Existing detection methods rely on heuristics

Neural Network-Driven Volatility Drag Mitigation under Aggressive Leverage

model-releasesarxiv-cs-lg

arXiv:2607.23068v1 Announce Type: cross Abstract: This paper introduces a compact reformulation of a modular end-to-end neural network for global minimum-variance portfolio optimization that decouples

Applications

Neural operator discovery from heterogeneous trajectories

arXiv:2607.23337v1 Announce Type: new Abstract: Neural operators provide data-driven mappings for modeling dynamical systems. Extending them to families of systems typically requires explicit conditio

applicationsarxiv-cs-lg

Neural Representation of Minimal Surfaces

arXiv:2607.23437v1 Announce Type: cross Abstract: We propose a neural representation for minimal surfaces. Unlike prior approaches based on discretization or Physics-Informed Neural Networks (PINNs),

Industry

Neuralink just shared that participants living with paralysis are now controlling a powered wheelchair using nothing but their thoughts. No …

Neuralink just shared that participants living with paralysis are now controlling a powered wheelchair using nothing but their thoughts. No joystick. Just intention. Next up Neuralink will likely conn

industryelon-musk--x

NeurGO: Learning to Generate Elite Candidates for Meta-Black-Box Expensive Optimization

arXiv:2607.23408v1 Announce Type: new Abstract: Expensive black-box optimization is ubiquitous in science and engineering, where function evaluations are costly and the evaluation budget is limited. T

NeurIPS 2026 AI-generated reviews [D]

researchr-machinelearning

I'm really confused about what the point of the prompt injection was (speaking as an author). Is it just a study? I would really prefer that they took action against the AI-generated reviews. Obviousl

NeurIPS 2026 Reviewer: AI-Generated Rebuttals (and Paper) [D]

model-releasesr-machinelearning

One of the papers I reviewed has what seems to be entirely LLM-generated rebuttals, and the original paper is also clearly LLM-generated, with Claude-speak everywhere. While the authors acknowledge LL

Neuro-Symbolic Meta-Policies for Temporal Knowledge-Graph Memory under Partial Observability

arXiv:2607.18368v2 Announce Type: replace Abstract: Partially observable reinforcement learning requires deciding what to retain, retrieve, and forget over time. We introduce a neuro-symbolic meta-pol