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Multi-Agentic System Leveraging Open-Source LLMs to Mitigate Disinformation Threats

model-releasesarxiv-cs-cl

arXiv:2606.30259v1 Announce Type: new Abstract: In contemporary societies, the threat of disinformation has reached alarming levels, exacerbated by the proliferation of electronic communication, socia

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Multi-Block Diffusion Language Models

DGX agent

arXiv:2606.29215v1 Announce Type: cross Abstract: Block Diffusion Language Models (BD-LMs) improve diffusion-based text generation with KV caching and flexible-length generation. A natural next step i

researcharxiv-cs-cl

30 Jun 2026

Multi-Class Human/Object Detection on Robot Manipulators using Proprioceptive Sensing

arXiv:2508.02425v2 Announce Type: replace-cross Abstract: In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments. Robots must analyze inte

Multi-Contact Force Estimation for Continuum Robots via Gaussian-Parameterized Factor Graphs

arXiv:2606.29165v1 Announce Type: new Abstract: Continuum robots offer key advantages in navigating unstructured environments, but their safe operation requires accurate estimation of the external con

researcharxiv-cs-ro

Multi-Level Distributional Entropy for Explainable Network Intrusion Detection

arXiv:2606.29797v1 Announce Type: cross Abstract: Machine learning network intrusion detection systems (IDS) rely on aggregate flow statistics that discard distributional structure, while established

researcharxiv-cs-ai

Multi-scale Object-Aware Gaze Estimation via Geometric Reasoning

arXiv:2606.29334v1 Announce Type: new Abstract: Gaze target estimation aims to predict the semantic object an observer fixates upon within an image, a task deeply rooted in the object-oriented nature

Multi-UAV Formation Cooperative Obstacle Avoidance and Adaptive Shape Deformation Control in Complex Environments Based on BI-APF-RRT and Affine Transformation

arXiv:2606.29755v1 Announce Type: new Abstract: Aiming at the problem that obstacle avoidance flexibility and formation integrity are difficult to coexist in multi-UAV formation motion in complex obst

researcharxiv-cs-ro

Local Ai

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models

arXiv:2606.28369v1 Announce Type: cross Abstract: Semantic search and recommendation of similar documents, such as news and reports about unusual environmental events (e.g., a dead whale washed ashore

local-aiarxiv-cs-ai

Multimodal Graph RAG for Long-range Visually Rich Document Understanding

arXiv:2606.28780v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, comprehending long documents remains an issue b

Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement

arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o

safetyarxiv-cs-cv

Multimodal Mathematical Reasoning with Diverse Solving Perspective

model-releasesarxiv-cs-cl

arXiv:2507.02804v2 Announce Type: replace Abstract: Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especial

Multimodal Representation Alignment for Cross-modal Information Retrieval

arXiv:2506.08774v2 Announce Type: replace-cross Abstract: Different machine learning models can represent the same underlying concept in different ways. This variability is particularly valuable for i

Multiplicative Oracle Inequalities for Transductive Learning via Level-Set Aggregation

arXiv:2603.02043v2 Announce Type: replace Abstract: We revisit transductive learning where predictions are made with the set of all covariates known in advance. In the leave-one-out (LOO) setting, the

Multiply Robust Causal Mediation Analysis with Continuous Treatments

model-releasesarxiv-cs-lg

arXiv:2105.09254v4 Announce Type: replace-cross Abstract: In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interes

Muon learns balanced solutions in matrix factorization without slow saddle-to-saddle dynamics

model-releasesarxiv-cs-lg

arXiv:2606.30509v1 Announce Type: new Abstract: Matrix factorization (i.e., problems of the form min_{mathbf{P},mathbf{Q}} |mathbf{M}^star - mathbf{P}^opmathbf{Q}|_F^2) is a minimal learning problem t

MuonSSM: Orthogonalizing State Space Models for Sequence Modeling

arXiv:2606.30461v1 Announce Type: new Abstract: State space models (SSMs) have emerged as efficient linear-time alternatives to attention for long-sequence modeling. However, existing SSMs often suffe

Tutorials

Mural: Transferring LLM knowledge to image generation via Mixture-of-Transformers

arXiv:2606.29013v1 Announce Type: new Abstract: Leveraging capabilities of large language models (LLMs) in text-to-image (T2I) synthesis is an important research direction. In this work we investigate

tutorialsarxiv-cs-cv

MUSE: Unlocking Timestep as Native Task Steering for One-Step Dense Prediction

arXiv:2606.30370v1 Announce Type: new Abstract: Monocular dense prediction has recently seen remarkable success by repurposing pre-trained diffusion models. This opens a promising yet challenging aven

MuseBench: Benchmarking Intent-Level Audiovisual Arts Understanding in MLLMs

model-releasesarxiv-cs-ai

arXiv:2606.30026v1 Announce Type: cross Abstract: Audiovisual arts encompass diverse creative disciplines, including cinema, visual arts, stage performance, and game design, where artistic meaning ari

Local Ai

MyGO-Splat: Multi-Objective Closed-Loop Geometric Feedback for RGB-Only Gaussian SLAM

arXiv:2606.29738v1 Announce Type: new Abstract: Real-time monocular Simultaneous Localization and Mapping (SLAM) fundamentally suffers from scale ambiguity and a lack of geometric self-correction. Whi

local-aiarxiv-cs-ro

NaLA: A 3D Native LLM Layout Agent for High-quality 3D Scene Generation

arXiv:2606.29395v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have emerged as promising layout agents for 3D scene generation. Existing layout agents still suffer from implaus

agentsarxiv-cs-cv

Negative Stepsizes Make Gradient-Descent-Ascent Converge

arXiv:2505.01423v2 Announce Type: replace-cross Abstract: Efficient computation of min-max problems is a central question in optimization, learning, games, and control. Arguably the most natural algor

Nemotron-Labs-Diffusion-Image: Advancing Masked Discrete Diffusion for High-Resolution Image Synthesis

arXiv:2606.29814v1 Announce Type: new Abstract: We propose Nemotron-Labs-Diffusion-Image, a state-of-the-art masked discrete diffusion model (MDM) for high-resolution text-to-image synthesis. Compared

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

Local Ai

Neural Gate: Mitigating Privacy Risks in LVLMs via Neuron-Level Gradient Gating

arXiv:2603.12598v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in crit

local-aiarxiv-cs-cv

Neural Minimum Weight Perfect Matching for Quantum Error Codes

arXiv:2601.00242v2 Announce Type: replace-cross Abstract: Realizing the full potential of quantum computation requires Quantum Error Correction (QEC). QEC reduces error rates by encoding logical infor

researcharxiv-cs-ai

Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering

arXiv:2606.29824v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires con

agentsarxiv-cs-ai

Neural Stereo Video Compression with Hybrid Disparity Compensation

arXiv:2504.20383v3 Announce Type: replace Abstract: Disparity compensation represents the primary strategy in stereo video compression (SVC) for exploiting cross-view redundancy. These mechanisms can

agentsarxiv-cs-cv

Neural Subspace Reallocation: Continual Learning as Retrieval-Based Subspace Memory Management

model-releasesarxiv-cs-ai

arXiv:2606.30067v1 Announce Type: cross Abstract: We introduce Neural Subspace Reallocation (NSR), which reframes continual learning as memory management over parameter subspaces. Instead of treating

NeuralMUSIC: A Hybrid Neural-Subspace Framework for Robot Sound Source Localization

arXiv:2606.18664v2 Announce Type: replace-cross Abstract: Reliable sound source localization is fundamental to robot audition, enabling autonomous robots to perceive spatial cues and operate effective

agentsarxiv-cs-ai

NeuReasoner: Theory-grounded Mapping of Reasoning Elicitation Boundaries

arXiv:2606.29971v1 Announce Type: new Abstract: A growing body of work suggests that the reasoning capabilities of large language models are largely latent in their base form, with post-training prima

Neuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation

arXiv:2606.28600v1 Announce Type: cross Abstract: Neuromorphic and edge computing research has focused on reducing the inference cost of neural network controllers, yet in physical closed-loop systems

Never Skip a Batch: Dense Learning of Temporal GNNs via Adaptive Pseudo-Supervision

model-releasesarxiv-cs-lg

arXiv:2505.12526v2 Announce Type: replace Abstract: Temporal graph networks suffer from irregular supervision in realworld dynamic graphs, as most minibatches contain few labeled events. The lack of l

New methods to compute the generalized chi-square distribution

arXiv:2404.05062v4 Announce Type: replace-cross Abstract: We present four new mathematical methods, two exact and two approximate, along with open-source software, to compute the cdf, pdf and inverse

Tutorials

NIVA: A Multimodal Foundation Model for Actionable Earth System Intelligence

arXiv:2606.28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost. However, existing data-driven

tutorialsarxiv-cs-lg

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection

arXiv:2606.30009v1 Announce Type: new Abstract: Graph anomaly detection (GAD) on text-attributed graphs (TAGs) is vital for applications such as fraud detection and academic integrity verification. Ex

safetyarxiv-cs-cl

NoiseTilt: Noise-Tilted Reverse Kernels for Diffusion Reward Alignment

arXiv:2606.18066v2 Announce Type: replace Abstract: We introduce the Noise-Tilted Reverse Kernel (NTRK), a reward-guided diffusion sampler that injects reward gradients through the noise term, leaving

safetyarxiv-cs-lg

Non-parametric recovery of causal diffusion mechanisms from steady-state observations

arXiv:2606.30467v1 Announce Type: cross Abstract: We consider sparse multivariate stochastic systems that evolve in continuous time according to a causal mechanism and present methodology to recover t

Nonlinear mixture model motivated subspace clustering

arXiv:2606.29261v1 Announce Type: cross Abstract: We derive the linear union-of-subspaces (UoS) model for subspace clustering (SC) from the nonlinear mixture model (NMM) used in blind source separatio

Normalizing Flow-Enhanced Message Passing for Multirobot Collaborative Localization

arXiv:2606.29868v1 Announce Type: new Abstract: Accurate, robust, and adaptive localization is essential for various robotic operations. This paper proposes a new message passing (MP) algorithm for re

agentsarxiv-cs-ro

Not All Objectives Are Born Equal: Priority-Constrained Descent for Hierarchical Multi-Objective Optimization

arXiv:2606.29521v1 Announce Type: new Abstract: Deep learning problems rarely involve objectives that are equal in importance. A primary objective defines the goal, whilst secondary objectives, such a

Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions

arXiv:2602.21160v4 Announce Type: replace-cross Abstract: In safety-critical classification, the cost of failure is often asymmetric, yet Bayesian deep learning summarises epistemic uncertainty with a

safetyarxiv-cs-lg

Not-quite-human tastes: the stylized omnivorousness of LLM survey surrogates

model-releasesarxiv-cs-cl

arXiv:2606.30085v1 Announce Type: new Abstract: Large-language models have proven to be remarkable if inconsistent parrots of public attitudes and opinions. The extent to which LLMs are able to produc

Notes on generative modeling: flow matching, diffusion, optimal transport and Schr{odinger bridge

arXiv:2606.30053v1 Announce Type: cross Abstract: These notes recapitulate the high level mathematical principles behind different techniques for generative modeling. I show the connections between op

Obliviate: Erasing Concepts from Autoregressive Image Generation Models

arXiv:2606.28643v1 Announce Type: new Abstract: The widespread adoption of generative AI models has intensified concerns about misuse, including the creation of unsafe or disturbing imagery. To mitiga

Applications

Occlusion-Robust Multi-Object Decoupling for Physics-Based Interaction

arXiv:2606.29303v1 Announce Type: new Abstract: We propose a mask-free method for lossless multi-object 3D reconstruction from sparse and occluded real-world views, enabling physically plausible inter

applicationsarxiv-cs-cv

Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment

arXiv:2601.22823v2 Announce Type: replace-cross Abstract: We study offline reinforcement learning of style-conditioned policies using explicit style supervision via subtrajectory labeling functions. I

OGM-CBF: Occupancy Grid Map-based Control Barrier Function for Safe Mobile Robot Control with Memory of out of View Obstacles

arXiv:2405.10703v4 Announce Type: replace Abstract: Safe control in unknown environments is a key challenge in mobile robotics. Control Barrier Functions (CBFs) provide a principled framework for guar

safetyarxiv-cs-ro