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Research

Measure Neural Mappings

DGX agent

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

researcharxiv-cs-lg

14 Oct 2026

Research

Measuring all the noises of LLM Evals

DGX agent

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

Search: “research”

Measure Neural Mappings

Measuring all the noises of LLM Evals

Measuring Variable Importance Using Proportional Inclusive Marginal Effects

MedEvo: Medical Reasoning Evolution through Knowledge Navigation

MERIT: Scaling KG Foundation Models with Relation Transformers

Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices

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

MFG: Multi-turn Feedback Guided Molecular Optimization

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

Minimax Rates and Improved Spectral Convergence for Multi-Manifold Clustering

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

Minimum Volume Optimal Transport for Multivariate Conformal Prediction

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

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

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

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

Mode Collapse of Mean-Field Variational Inference

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

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

Moment-Based Anomaly Detection in High-Dimensional Mixed Data

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

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

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

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

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

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

Naga: Vedic Encoding for Deep State Space Models

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

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

Neural-Surrogate Co-Design of Aerodynamic Shape and Control

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

NFMap: Topographic 2D Manifold Learning with Invertible Normalizing Flows

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

Non-Euclidean Gradient Descent Has Many Edges of Stability

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

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

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

Novel View Synthesis using DDIM Inversion

OceanFlow: Coherent Flow Matching for Probabilistic Ocean Modeling

OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows

On Collusion-Free Teaching in Planar Graphs

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

On physical implementability of reinforcement-learning-driven reasoning

On Sleep-Wake Disorder Identification from Polysomnographic Representations

On the Calibration of Crowdsourcing Aggregators

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

On the Theoretical Limits of Learning Unconstrained Interatomic Potentials

One Model, Multiple Compute Budgets: Multi-Ratio ConceptMoE for Flexible Compute Across Turns