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Modern Backbones Improve Multi-task DETR for Mammography Classification and Lesion Localization

arXiv:2608.09801v1 Announce Type: cross Abstract: Joint exam-level prediction and candidate-region localization may improve the usefulness of AI support in mammography. We study this setting using a m

local-aiarxiv-cs-ai

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Research

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs

DGX agent

arXiv:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)

researcharxiv-cs-cl

11 Aug 2026

MonitorBench: A Comprehensive Benchmark for Chain-of-Thought Monitorability in Large Language Models

arXiv:2603.28590v3 Announce Type: replace Abstract: Large language models (LLMs) can generate chains of thought (CoTs) that are not always causally responsible for their final outputs. When such a mis

MoNo: Multiscale Optimal Transport Neural Operator for Solving PDEs on General Geometries

arXiv:2608.09764v1 Announce Type: cross Abstract: Transformer-based neural operators have achieved substantial progress in solving Partial Differential Equations (PDEs) by projecting spatial observati

Monotonicity-Guided Bottom-Up Petri Net Discovery: The SPECpp Framework

arXiv:2608.09398v1 Announce Type: cross Abstract: Process discovery is one of the central challenges in process mining. Petri nets are particularly attractive because simple local constructs can expre

MoRSE: Task-Oriented Multi-Agent System with Mixture of Role-Subtask Experts

arXiv:2608.09251v1 Announce Type: cross Abstract: Large language model-based multi-agent systems have recently shown strong potential for complex, long-horizon tasks. However, existing methods mainly

MOSAIC: Adversarial Co-evolution of Specialist Heuristics and Problem Instances for LLM-based Automated Heuristic Design

arXiv:2608.07544v1 Announce Type: cross Abstract: Automated heuristic design (AHD) with large language models (LLMs) has produced strong heuristics for combinatorial optimization problems (COPs). Yet

Motif 3: Technical Report

arXiv:2608.09119v1 Announce Type: new Abstract: We introduce Motif 3, a decoder-only Mixture-of-Experts language model with 314 billion total parameters and 13.2 billion activated per token. Each spar

Applications

Motion-Aware Animatable Gaussian Avatars Deblurring

arXiv:2411.16758v4 Announce Type: replace Abstract: The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely

applicationsarxiv-cs-cv

MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling

arXiv:2608.08553v1 Announce Type: new Abstract: Video super-resolution (VSR) aims to recover high-fidelity high-resolution videos from low-resolution inputs and is central to applications ranging from

safetyarxiv-cs-cv

MPISuperRes-PnP: A Super-Resolution Zero-Shot Plug-and-Play Reconstruction Algorithm for Magnetic Particle Imaging

arXiv:2608.09672v1 Announce Type: new Abstract: Magnetic Particle Imaging (MPI) is an emerging medical imaging modality. MPI is based on the non-linear response of magnetic nanoparticles to an applied

MPPI Planning with Gaussian Based Human Cost Function for Social Navigation

arXiv:2608.08323v1 Announce Type: new Abstract: Safe robot navigation in crowded spaces requires planning that accounts for where people will be, not only where they are now. Model Predictive Path Int

researcharxiv-cs-ro

MRBench: A Comprehensive Benchmark for Human Motion-Text Retrieval

arXiv:2608.07993v1 Announce Type: new Abstract: Human motion-text retrieval provides a rigorous means of assessing cross-modal alignment. Prevailing benchmarks are dominated by homogeneous indoor moti

MRI super-resolution in ten sampling steps using a diffusion bridge model

arXiv:2608.08819v1 Announce Type: new Abstract: Objective. MRI provides excellent soft-tissue contrast, but long acquisition times can cause patient discomfort and lead to motion artifacts, forcing a

MSP-Net: Manifold-Guided Spectral Prompt Network for Hyperspectral Object Tracking

arXiv:2608.09575v1 Announce Type: new Abstract: Hyperspectral object tracking leverages abundant spectral information to provide unique advantages for target discrimination in complex scenes. However,

Multi-Agent AI Safety as an Institutional Design Problem

arXiv:2608.09828v1 Announce Type: cross Abstract: AI agents increasingly work inside systems that govern how they delegate tasks, move information, execute actions, and use shared resources. Recent wo

Multi-agent discovery of practical quantum LDPC codes

arXiv:2608.08996v1 Announce Type: cross Abstract: Quantum low-density parity-check (qLDPC) codes can encode multiple logical qubits using sparse parity checks, yet searching for useful finite-length i

Multi-Agent Reinforcement Learning via Agent-Specific Preference

model-releasesarxiv-cs-lg

arXiv:2608.08604v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) is a powerful framework for solving complex collaborative tasks, but it relies heavily on well-defined global

Multi-Branch Policy Optimization for Multimodal Large Language Models

arXiv:2608.07581v1 Announce Type: cross Abstract: Group-based reinforcement learning methods for multimodal large language models typically rely on trajectory-level credit assignment that applies a si

Tutorials

Multi-Granular Node Pruning for Causal Circuit Discovery

arXiv:2512.10903v3 Announce Type: replace Abstract: Circuit discovery aims to identify minimal subnetworks that are responsible for specific behaviors in large language models (LLMs). Existing approac

tutorialsarxiv-cs-ai

Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery

arXiv:2608.08704v1 Announce Type: cross Abstract: Kernel spectral clustering with a single bandwidth can be inadequate for data exhibiting multiple characteristic pairwise-distance scales, a problem p

researcharxiv-cs-lg

Multi-modal Interactive Control of Robotic Arm based on Offline Large Language Models

arXiv:2608.08183v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly revolutionized the modern society with numerous advanced interactions between humans and AI agents, wher

local-aiarxiv-cs-ro

Tutorials

Multi-Relational Knowledge Graph Enhanced Embedding for Trajectory-User Linking

arXiv:2608.08646v1 Announce Type: cross Abstract: Trajectory-User Linking (TUL) aims to identify the owner of an anonymous trajectory from a set of candidate users, providing a basis for user mobility

tutorialsarxiv-cs-cv

Multi-Submap Implicit Neural SLAM with Local-to-Global Loop Closure for Large-Scale Scene Reconstruction

arXiv:2608.09146v1 Announce Type: new Abstract: Neural Radiance Fields (NeRF)-based SLAM has demonstrated impressive results in small-scale scene reconstruction, yet scaling these methods to extensive

local-aiarxiv-cs-cv

Multi-Task Consistency-based Detection of Adversarial Attacks

arXiv:2608.07750v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) have found successful deployment in numerous vision perception systems. However, their susceptibility to adversarial attac

Multilingual Agent-Based World Modeling for Social Science

arXiv:2512.07195v2 Announce Type: replace-cross Abstract: Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly mon

Multilingual Emotion Neurons in Large Audio-Language Models

arXiv:2608.08772v1 Announce Type: new Abstract: Emotion is central to human communication, and its expression varies across languages. Large audio-language models (LALMs) achieve strong performance on

researcharxiv-cs-cl

Multimodal Federated Learning under Dual-Axis Modality Missingness

arXiv:2608.09240v1 Announce Type: cross Abstract: Multimodal federated learning (FL) supports collaborative modeling in privacy-sensitive health-sensing and medical settings, but realistic deployments

local-aiarxiv-cs-ai

Multimodal Model Diffing for Feature Discovery and Control

arXiv:2608.09928v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to

Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion

arXiv:2608.07574v1 Announce Type: new Abstract: Skin lesion classification plays an important role in supporting the early diagnosis of skin cancer. However, automated analysis remains challenging due

MultiShadow: Multi-Object Shadow Generation for Image Compositing via Diffusion Model

arXiv:2603.02743v4 Announce Type: replace Abstract: Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and

safetyarxiv-cs-cv

Multitask Scanning Probe Microscopy

arXiv:2608.09104v1 Announce Type: cross Abstract: Scanning probe microscopy provides nanoscale access to structural, electrical, electromechanical, magnetic, and mechanical properties of materials. It

agentsarxiv-cs-lg

MusicLayout: Explicit Structural Planning for Controllable Text-to-Music Generation

arXiv:2608.09035v1 Announce Type: cross Abstract: Text-to-music generation has advanced rapidly, but current systems still rely primarily on global text prompts, leaving the structural organization of

MVMD: A Multi-View Approach for Enhanced Mirror Detection

arXiv:2608.07559v1 Announce Type: new Abstract: In 3D reconstruction, mirrors introduce significant challenges by creating distorted and fragmented spaces, resulting in inaccurate and unreliable 3D mo

NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams

arXiv:2608.09200v1 Announce Type: new Abstract: Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. H

NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs

arXiv:2608.08107v1 Announce Type: cross Abstract: Multimodal expansion of large language models (LLMs) enables new perceptual capabilities but often compromises the language intelligence acquired duri

Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks

arXiv:2608.08567v1 Announce Type: new Abstract: A central obstacle in building graph foundation models is the input heterogeneity in terms of feature space dimensionality, semantics, and structure. Su

safetyarxiv-cs-lg

Neural Operators for Immersed-Boundary Soft Swimmers Locomotion

model-releasesarxiv-cs-lg

arXiv:2608.07722v1 Announce Type: new Abstract: High-fidelity immersed-boundary simulation resolves the coupled motion of a deforming swimmer and its surrounding flow, but the resulting cost limits re

NeuralDMD: Interpretable Neural Representation of Dynamics from Sparse and Noisy Measurements

arXiv:2507.03094v2 Announce Type: replace Abstract: Many challenges in scientific imaging involve solving ill-posed inverse problems, where the goal is to recover spatio-temporal fields from indirect,

neuralGAM: An R Package for Fitting Generalized Additive Neural Networks

arXiv:2505.08610v2 Announce Type: replace-cross Abstract: Nowadays, Neural Networks are considered one of the most effective methods for various tasks such as anomaly detection, computer-aided disease

researcharxiv-cs-lg

NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning

arXiv:2510.18940v2 Announce Type: replace-cross Abstract: Existing parameter-efficient fine-tuning (PEFT) methods primarily fall into two categories: addition-based and selective in-situ adaptation. T

NeuroBreak: Unveil Internal Jailbreak Mechanisms in Large Language Models

arXiv:2509.03985v2 Announce Type: replace-cross Abstract: In deployment and application, large language models (LLMs) typically undergo safety alignment to prevent illegal and unethical outputs. Howev

NeuroGuard: Neural Gradient Update Aware of Representation Damage

arXiv:2608.08068v1 Announce Type: new Abstract: Long-tailed class-incremental learning (LT-CIL) must learn new classes from imbalanced streams while retaining old classes. Existing methods mainly chan

Neuronal Attention Circuit (NAC) for Representation Learning

arXiv:2512.10282v4 Announce Type: replace Abstract: Attention improves representation learning over RNNs, but its discrete nature limits continuous-time (CT) modeling. We introduce Neuronal Attention

NeuroPilot: An Agent-Driven Smart Pipeline for Processing, Quality Control, and Managing Neuroimages

arXiv:2608.07541v1 Announce Type: cross Abstract: Transforming raw neuroimage archives into analysis-ready derivatives relies on three brittle stages: data standardization, modality-specific preproces

NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation

arXiv:2608.09636v1 Announce Type: cross Abstract: Accurate 3D neuron segmentation in fluorescence microscopy is critical for neuroscience. However, the sparse and elongated morphology of neurons poses

Neurosymbolic Discovery of Algebraic Graph Constructions

arXiv:2608.08118v1 Announce Type: new Abstract: There are several methods for searching for graphs with prescribed properties, such as SAT solvers and specialized generators. These methods return the

NewtonGS: Physics-Structured Object-Level Neural Newtonian Dynamics for Gaussian Scene Animation

arXiv:2608.07598v1 Announce Type: new Abstract: Animating objects in a static 3D Gaussian scene requires an explicit object-level dynamic state and a controllable model of object motion. Existing dyna