Search: “research”

Masked Diffusion for Travel Diaries Synthesis

arXiv:2610.17109v1 Announce Type: new Abstract: Because household travel surveys combine household characteristics, variable-length person rosters, vehicle rosters, and trip chains, existing synthesis

Meaningful Moments: A Corpus of VLM-Derived Temporal Importance Labels for Video Action Recognition

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DGX agent

arXiv:2610.16009v1 Announce Type: new Abstract: Not every moment in a video is equally useful for recognizing an action. A few decisive moments often carry the evidence: the instant an object moves, t

researcharxiv-cs-cv

14 Oct 2026

Measure Neural Mappings

arXiv:2610.17384v1 Announce Type: new Abstract: We introduce and define measure neural mappings (MNMs), which combine measure-dependent neural transport with ensemble consistency for learning operator

Measuring all the noises of LLM Evals

arXiv:2512.21326v3 Announce Type: replace Abstract: Applying well-established statistical methods effectively to LLM evals requires consideration of model correlations and prediction noises. Leading e

Measuring Variable Importance Using Proportional Inclusive Marginal Effects

arXiv:2610.17053v1 Announce Type: cross Abstract: Shapley-based measures are widely used for measuring variable importance in statistics and machine learning. However, these measures have a serious is

MedEvo: Medical Reasoning Evolution through Knowledge Navigation

arXiv:2610.17690v1 Announce Type: cross Abstract: Medical multimodal reasoning models are typically trained on teacher-generated rationales, discarding the valid reasoning in students' own failed traj

MERIT: Scaling KG Foundation Models with Relation Transformers

arXiv:2610.15638v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models (KGFMs) predict links on unseen graphs zero-shot. KGFMs have been pioneered by ULTRA which builds a relation grap

Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices

arXiv:2509.22707v2 Announce Type: replace-cross Abstract: Dynamic Voltage and Frequency Scaling is essential for enhancing energy efficiency in mobile platforms. However, traditional heuristic-based g

Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning

arXiv:2610.14976v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have excelled in joint visual and language understanding, particularly in image captioning. However, LVLMs remain p

MFG: Multi-turn Feedback Guided Molecular Optimization

arXiv:2610.18851v1 Announce Type: cross Abstract: Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple

MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation

arXiv:2610.17354v1 Announce Type: new Abstract: Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which

Minimax Rates and Improved Spectral Convergence for Multi-Manifold Clustering

arXiv:2610.15892v1 Announce Type: cross Abstract: We study eigenpair estimation for the tensorized, density-weighted Laplace--Beltrami operator from n independent data points sampled from a multi-mani

Minimax rates for pointwise CATE estimation: the role of design smoothness

arXiv:2610.18623v1 Announce Type: cross Abstract: We study the role of design smoothness in the minimax estimation of conditional average treatment effects at a fixed covariate point. For design densi

Minimum Volume Optimal Transport for Multivariate Conformal Prediction

arXiv:2610.14907v1 Announce Type: cross Abstract: Optimal transport (OT) enables multivariate conformal prediction (CP) to construct flexible prediction sets that reflect the underlying complex distri

MIRRA: Fast, High-Fidelity Molecular Generation with Chemistry-Informed Discrete Flow Matching

arXiv:2610.17244v1 Announce Type: new Abstract: Fast, high-fidelity molecular generation requires accurate chemical choices and efficient sampling. Chemical building blocks reduce graph size, but make

MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series

arXiv:2610.17715v1 Announce Type: new Abstract: Flow matching has emerged as a powerful alternative to diffusion models for generative modeling, but standard conditional flow matching is fundamentally

Mitigating Black-Box Score-Based Query Attacks via Gradient Confusion

arXiv:2610.17382v1 Announce Type: new Abstract: Score-based black-box adversarial attacks pose a serious threat to deployed machine learning systems by exploiting repeated model queries to craft adver

Mobility-Budget-Constrained Submodular Maximization for Distributed Semantic Multi-Robot Exploration

arXiv:2610.17562v1 Announce Type: new Abstract: Multi-robot exploration under communication and mobility constraints requires balancing information gain with reachability. We present a distributed sem

Mode Collapse of Mean-Field Variational Inference

arXiv:2510.17063v2 Announce Type: replace-cross Abstract: Mean-field variational inference (MFVI) is a widely used method for approximating high-dimensional probability distributions by product measur

Modeling and Control of a Rigid-soft Hybrid-link Humanoid Robot

arXiv:2610.15073v1 Announce Type: new Abstract: Physical flexibility plays a significant role not only in human motions but also in robot motions. For example, a humanoid robot with passive and flexib

ModRes: A modification of the ResPlan dataset ready for floor plan analysis and graph machine learning

arXiv:2610.17178v1 Announce Type: new Abstract: Floor plan datasets underpin computational analysis of building layouts, spatial connectivity and graph machine learning. However, publicly available da

Moment-Based Anomaly Detection in High-Dimensional Mixed Data

arXiv:2610.16285v1 Announce Type: cross Abstract: We propose an anomaly detection method for high-dimensional mixed-type data that maps heterogeneous features to a common scale via standardized moment

Morphology-aware deep learning predicts colorectal cancer survival from whole-slide images

arXiv:2610.17603v1 Announce Type: new Abstract: Background: Five-year survival prediction from hematoxylin-and-eosin whole-slide images could support risk stratification, but the task is weakly superv

MP-MNCA: Morphology-Prior Masked Neighbor Cross-Attention for Efficient Spatial Domain Identification

arXiv:2610.16212v1 Announce Type: new Abstract: Spatial transcriptomics jointly captures molecular state, tissue morphology, and spatial organization, yet spatial-domain methods are typically compared

MRFlow: Mechanism-Structured Residual Flow Matching for Virtual Cell Perturbation Prediction

arXiv:2610.13966v1 Announce Type: new Abstract: Predicting cellular responses to chemical and genetic perturbations is a central test for AI virtual cells, yet many single-cell models reduce each cond

MSC: Multi-Stage Caster-aware Control Framework with Uncertainty-Aware NMPC and RL-based Execution Layer

arXiv:2610.16199v1 Announce Type: cross Abstract: Freely swiveling casters are widely adopted in industrial AMRs/SDVs for their mechanical simplicity and load capacity. However, caster misalignment du

Multi-Token Random-Walk Learning via Meeting-Triggered Information Exchange

arXiv:2610.14716v1 Announce Type: new Abstract: Random walk (RW)-based algorithms are widely used in decentralized learning due to their low communication overhead and scalability. While most existing

Multiclass histogram-based thresholding using kernel density estimation and scale-space representations

arXiv:2202.04785v2 Announce Type: replace-cross Abstract: We present a method for multiclass thresholding of histograms whose modes may overlap so strongly that they merge into a unimodal distribution

Naga: Vedic Encoding for Deep State Space Models

arXiv:2511.13510v2 Announce Type: replace Abstract: This paper presents Naga, a deep State Space Model (SSM) encoding approach inspired by structural concepts from Vedic mathematics. The proposed meth

nanoflann: A Header-Only KD-Tree Library for Exact Nearest-Neighbor Search on Compile-Time Product Manifolds

arXiv:2610.15215v1 Announce Type: new Abstract: Nearest-neighbor (NN) search underlies countless robotics algorithms, but many state spaces are not Euclidean: orientations live on SO(2) or SO(3) and p

Nearest Neighbor Functional Curve Completion for Intraday Probabilistic Revisions of Renewable Generation Forecasts

arXiv:2610.17075v1 Announce Type: new Abstract: We propose a nonparametric approach that fuses deterministic initial forecasts and a partial realization into a probabilistic forecast using the framewo

Neural-Surrogate Co-Design of Aerodynamic Shape and Control

arXiv:2603.06760v2 Announce Type: replace Abstract: Control co-design jointly optimizes a robot's physical design and its controller. Existing techniques are limited in the number of model parameters

Neuromorphic Decoding and Dynamical Image Reconstruction from Populations of Spiking Retinal Ganglion Cells

arXiv:2610.17154v1 Announce Type: cross Abstract: Decoding visual stimuli from the spiking activity of retinal ganglion cells (RGCs) informs both our understanding of the retinal code and the design o

NFMap: Topographic 2D Manifold Learning with Invertible Normalizing Flows

arXiv:2610.16750v1 Announce Type: new Abstract: We present NFMap, a dimensionality reduction method for 2D visualisation that extends Generative Topographic Mapping (GTM) with a bijective normalizing

Noise2Match: Self-Supervised Low-Dose CT Denoising via Adaptive Inter-Slice Matching

arXiv:2610.18379v1 Announce Type: new Abstract: With the rapid development of deep learning, supervised convolutional neural network methods have greatly improved the performance of low-dose computed

Non-Euclidean Gradient Descent Has Many Edges of Stability

arXiv:2610.15223v1 Announce Type: cross Abstract: Recent observations that deep learning models train at the edge of stability have renewed interest in understanding stability properties of classical

Not All Challenges Are Equal: Evaluating Interactive Liveness Detection Against Real-Time Face Swaps

arXiv:2610.16417v1 Announce Type: new Abstract: Remote identity verification assumes that a camera stream shows a live person, yet public real-time face-swap tools can replace that person before the s

Not All Drift Is a Mechanism: Tracing Prompt Adaptation in LLMs

arXiv:2610.18412v1 Announce Type: new Abstract: Prompt-based adaptation offers several ways to specialize a frozen language model, ranging from natural-language prompt optimization to learned continuo

Not Every Cue Is Evidence: Cue Supportability for Forensic Distillation in Face Forgery Detection

arXiv:2610.16452v1 Announce Type: new Abstract: Explainable face forgery detection requires not only correct judgments but also forensic evidence supported by the input image. However, training cues a

Novel View Synthesis using DDIM Inversion

arXiv:2508.10688v3 Announce Type: replace Abstract: Single-image novel view synthesis requires viewpoint-dependent structural changes while retaining source-scene information and inferring unobserved

OceanFlow: Coherent Flow Matching for Probabilistic Ocean Modeling

arXiv:2610.15518v1 Announce Type: new Abstract: Probabilistic ocean modeling is essential for risk-aware marine operations, climate analysis, and scientific decision-making, where downstream decisions

OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows

arXiv:2610.16586v1 Announce Type: new Abstract: Generating accurate 3D molecules requires jointly determining a variable number of atoms, their identities, and geometry across spatial scales: global s

On Collusion-Free Teaching in Planar Graphs

arXiv:2610.18714v1 Announce Type: cross Abstract: Non-clashing teaching minimizes teaching complexity among models satisfying the Goldman--Mathias collusion-avoidance criterion. While the Vapnik--Cher

On Generalizing Preference-based Reinforcement Learning to Multi-Objective Problems

arXiv:2607.11432v2 Announce Type: replace Abstract: We study reinforcement learning (RL) from pairwise human-generated trajectory comparisons. We generalize preference-based RL by formalizing a novel

On physical implementability of reinforcement-learning-driven reasoning

arXiv:2610.14131v1 Announce Type: cross Abstract: In the machine learning community, the reinforcement-learning-driven reasoning process has been intensively studied since around 2025. In this article

On Sleep-Wake Disorder Identification from Polysomnographic Representations

arXiv:2610.17451v1 Announce Type: new Abstract: Self-supervised polysomnography foundation models (PSG FMs) aim to capture clinically useful information beyond sleep staging, yet are rarely compared w

On the Calibration of Crowdsourcing Aggregators

arXiv:2610.16815v1 Announce Type: cross Abstract: Calibration has been extensively studied for classifiers, but remains largely unexplored for crowdsourcing aggregation methods, which are increasingly

On the Optimality of Random Features under General Conditions: Misspecified Cases and Robust Learning

arXiv:2610.18333v1 Announce Type: cross Abstract: Random features provide a standard approach to scaling kernel methods to large datasets by approximating the kernel with a finite-dimensional feature