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MMGS: 10imes Compressed 3DGS through Optimal Transport Aggregation based on Multi-view Ranking

arXiv:2605.19304v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it suffers from significant overhead due to massive redundant primitives. Exist

researcharxiv-cs-cv

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Agents

MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent

DGX agent

arXiv:2605.19194v1 Announce Type: new Abstract: The Mixture-of-Agents (MoA) framework has shown promise in improving large language model (LLM) performance by aggregating outputs from multiple agents.

agentsarxiv-cs-cl

20 May 2026

MO-CAPO: Multi-Objective Cost-Aware Prompt Optimization

arXiv:2605.18869v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance across a wide range of tasks but are highly sensitive to prompt design, motivating the need fo

Agents

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization

arXiv:2605.19330v1 Announce Type: new Abstract: LLM agents organize behavior through skills - structured natural-language specifications governing how an agent reasons, retrieves, and responds. Unlike

agentsarxiv-cs-ai

MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks

arXiv:2605.18919v1 Announce Type: cross Abstract: Evolutionary algorithms for adversarial attacks leverage population-based search to discover perturbations without gradient information, but suffer fr

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

arXiv:2403.07183v4 Announce Type: replace-cross Abstract: We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a lar

applicationsarxiv-cs-ai

Motion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations

arXiv:2412.13111v2 Announce Type: replace Abstract: Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods of

researcharxiv-cs-cv

MotionMERGE: A Multi-granular Framework for Human Motion Editing, Reasoning, Generation, and Explanation

arXiv:2605.18956v1 Announce Type: new Abstract: Recent motion-language models unify tasks like comprehension and generation but operate at a coarse granularity, lacking fine-grained understanding and

MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification

model-releasesarxiv-cs-lg

arXiv:2605.19752v1 Announce Type: new Abstract: Accurately identifying metabolites i.e. small molecules from mass spectrometry data remains a core challenge in metabolomics, with broad applications in

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

arXiv:2605.20183v1 Announce Type: new Abstract: Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However,

MTraining: Distributed Dynamic Sparse Attention for Efficient Ultra-Long Context Training

model-releasesarxiv-cs-cl

arXiv:2510.18830v2 Announce Type: replace Abstract: The adoption of long context windows has become a standard feature in Large Language Models (LLMs), as extended contexts significantly enhance their

Multi-axis Analysis of Image Manipulation Localization

arXiv:2605.20174v1 Announce Type: new Abstract: Advanced image editing software enables easy creation of highly convincing image manipulations, which has been made even more accessible in recent years

Agents

Multi-Headed Transformer Architectures as Time-dependent Wasserstein Gradient Flows

arXiv:2605.18870v1 Announce Type: new Abstract: In recent years, transformer architectures have revolutionized the field of language processing, opening the door to previously unforeseen possibilities

agentsarxiv-cs-lg

Multi-Pedestrian Safety Warning at Urban Intersections Use Case of Digital Twin

arXiv:2605.18823v1 Announce Type: new Abstract: Digital twins (DTs) for urban transportation systems have gained increasing attention; however, their systematic evaluation in safety-critical scenarios

local-aiarxiv-cs-lg

Multi-Scale Generative Modeling with Heat Dissipation Flow Matching

arXiv:2605.19371v1 Announce Type: cross Abstract: Diffusion models are widely used in image generation, with most relying on noise-based corruption and denoising. A distinct branch instead uses blur a

Multi-Session Ground Texture SLAM in Low-Dynamic Environments

arXiv:2605.19701v1 Announce Type: new Abstract: The simultaneous localization and mapping community has introduced a growing number of systems adapted for multi-session operations where the operationa

safetyarxiv-cs-ro

Multi-Token Residual Prediction

arXiv:2605.18817v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) generate text by iteratively denoising masked token sequences, offering a tradeoff between parallelism and quality comp

applicationsarxiv-cs-lg

Multilayer Correlation Clustering

arXiv:2404.16676v2 Announce Type: replace-cross Abstract: We establish Multilayer Correlation Clustering, a novel generalization of Correlation Clustering to the multilayer setting. In this model, we

applicationsarxiv-cs-lg

Multimodal system for skin cancer detection

arXiv:2601.14822v2 Announce Type: replace-cross Abstract: Melanoma detection is vital for early diagnosis and effective treatment. While deep learning models on dermoscopic images have shown promise,

applicationsarxiv-cs-ai

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs

arXiv:2511.14159v2 Announce Type: replace Abstract: Evaluating the robustness of Large Vision-Language Models (LVLMs) is essential for their continued development and responsible deployment in real-wo

Navigating the Emotion Tree: Hierarchical Hyperbolic RAG for Multimodal Emotion Recognition

arXiv:2605.18884v1 Announce Type: cross Abstract: Multimodal emotion recognition aims to integrate text, audio, and video sources to understand human affective states. Although multimodal large langua

researcharxiv-cs-cv

Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies

arXiv:2507.06428v2 Announce Type: replace-cross Abstract: We mathematically analyze and numerically study an actor-critic machine learning algorithm for solving high-dimensional Hamilton-Jacobi-Bellma

Neural Configuration-Space Barriers for Manipulation Planning and Control

arXiv:2503.04929v3 Announce Type: replace-cross Abstract: Planning and control for high-dimensional robot manipulators in cluttered dynamic environments require computational efficiency and robust saf

safetyarxiv-cs-lg

Neural Network Models for Contextual Regression

arXiv:2603.24400v2 Announce Type: replace-cross Abstract: We propose a neural network model for contextual regression in which the regression model depends on contextual features that determine the ac

Neural Operators for Design-Space Surrogate Modeling of Tendon-Actuated Continuum Robots

arXiv:2605.19104v1 Announce Type: cross Abstract: Continuum robots enable dexterous manipulation in constrained environments, but require accurate and efficient models for real-time manipulation and c

Agents

Neuromorphic Control of a Flapping-Wing Robot on Resource-Constrained Hardware

arXiv:2605.19430v1 Announce Type: new Abstract: Flapping-Wing Micro Aerial Vehicles (FWMAVs) provide exceptional maneuverability and aerodynamic efficiency but pose significant challenges for onboard

agentsarxiv-cs-ro

Neuron Incidence Redistribution for Fairness in Medical Image Classification

arXiv:2605.19393v1 Announce Type: new Abstract: Deep learning models for medical image classification are susceptible to subgroup performance disparities across demographic attributes such as age, gen

safetyarxiv-cs-cv

Tutorials

Neurosymbolic Learning for Inference-Time Argumentation

arXiv:2605.20098v1 Announce Type: new Abstract: Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or

tutorialsarxiv-cs-ai

Next-Acceleration-Scale Prediction for Autoregressive MRI Reconstruction

arXiv:2605.19354v1 Announce Type: cross Abstract: MRI reconstruction is an inherently ill-posed inverse problem, since incomplete measurements admit many plausible solutions. This ambiguity becomes mo

NGL: Natural Garment Language for Training-Free Sewing Pattern Estimation

arXiv:2602.20700v2 Announce Type: replace Abstract: Estimating sewing patterns from images is a practical approach for creating high-quality 3D garments, but it remains challenging due to the scarcity

No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degrading Zero-shot Capabilities of Contrastive Models

arXiv:2603.25722v2 Announce Type: replace Abstract: Contrastive vision-language (V&L) models remain a popular choice for various applications. However, several limitations have emerged, most notably t

Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients

arXiv:2510.18924v3 Announce Type: replace-cross Abstract: Reinforcement learning from human feedback (RLHF) or verifiable rewards (RLVR), the standard paradigm for aligning LLMs or building recent SOT

safetyarxiv-cs-ai

Noise scheduling and linear dynamics in diffusion models on Lie groups

arXiv:2605.17326v1 Announce Type: cross Abstract: We investigate the role of the noise schedule in diffusion processes on Lie groups, with particular emphasis on applications to lattice gauge theory.

Nonlinearity as Rank: Generative Low-Rank Adapter with Radial Basis Functions

model-releasesarxiv-cs-ai

arXiv:2602.05709v2 Announce Type: replace Abstract: Low-rank adaptation (LoRA) approximates the update of a pretrained weight matrix using the product of two low-rank matrices. However, standard LoRA

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

arXiv:2512.04452v2 Announce Type: replace-cross Abstract: NORi is a machine learning (ML) parameterization of ocean boundary layer turbulence that is physics-based and augmented with neural networks.

local-aiarxiv-cs-ai

Normative Networks for Source Separation via Local Plasticity and Dendritic Computation

arXiv:2605.19965v1 Announce Type: new Abstract: Blind source separation (BSS) is a natural framework for studying how latent causes may be recovered from sensory mixtures, but deriving online and biol

Not All Tokens Are Worth Caching: Learning Semantic-Aware Eviction for LLM Prefix Caches

model-releasesarxiv-cs-lg

arXiv:2605.18825v1 Announce Type: new Abstract: Prefix caching is a key optimization in Large Language Model (LLM) serving, reusing attention Key-Value (KV) states across requests with shared prompt p

Not all uncertainty is alike: volatility, stochasticity, and exploration

arXiv:2605.19215v1 Announce Type: new Abstract: Adaptive decision-making in biological and artificial intelligence requires balancing the exploitation of known outcomes with the exploration of uncerta

safetyarxiv-cs-ai

Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR

arXiv:2605.20164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has made post-training highly effective when correctness can be checked automatically. However, many impo

safetyarxiv-cs-ai

OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences

arXiv:2605.18930v1 Announce Type: cross Abstract: Memory-augmented large language model (LLM) agents use iterative reflection and self-evolution to solve complex tasks, but these mechanisms introduce

local-aiarxiv-cs-ai

OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments

model-releasesarxiv-cs-ai

arXiv:2605.18758v1 Announce Type: cross Abstract: Current benchmarks for graphical user interface (GUI) agents predominantly rely on static screenshots. However, real-world smartphone interaction rout

On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosis

arXiv:2605.19201v1 Announce Type: cross Abstract: Deep learning models detect pneumonia from chest X-rays with high accuracy, but the performance declines under domain shifts caused by differences in

local-aiarxiv-cs-ai

On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization

model-releasesarxiv-cs-lg

arXiv:2601.12238v4 Announce Type: replace-cross Abstract: In this paper, we provide a comprehensive theoretical analysis of Stochastic Gradient Descent (SGD) and its momentum variants (Polyak Heavy-Ba

One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer

arXiv:2511.22940v3 Announce Type: replace Abstract: Recent advances in diffusion models have greatly improved pose-driven character animation. However, existing methods are limited to spatially aligne

safetyarxiv-cs-cv

Online Market Making and the Value of Observing the Order Book

arXiv:2605.19584v1 Announce Type: new Abstract: We study an online market-making problem in which a learner sequentially posts bid and ask prices for a single asset while interacting with traders hold

Tutorials

OP2GS: Object-Aware 3D Gaussian Splatting with Dual-Opacity Primitives

arXiv:2605.20044v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) provides an explicit and efficient scene representation, but its primitives lack inherent object-level identity, hindering

tutorialsarxiv-cs-cv

Open-Set Domain Adaptation Under Background Distribution Shift: Challenges and A Provably Efficient Solution

arXiv:2512.01152v4 Announce Type: replace-cross Abstract: As we deploy machine learning systems in the real world, a core challenge is to maintain a model that is performant even as the data shifts. S

applicationsarxiv-cs-ai

OpenCompass: A Universal Evaluation Platform for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.19276v1 Announce Type: new Abstract: In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large lang