Search: “research”

Loading history and window geometry bound compact-state slip ranking during granular shear startup

arXiv:2610.00124v1 Announce Type: cross Abstract: Granular slip forecasting can conflate material state, loading progress, and the geometry of event-centered sampling. We separated these contributions

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Research

Localizing Transfer Between Memorization Tasks

DGX agent

arXiv:2610.00771v1 Announce Type: new Abstract: A central puzzle in transfer learning is why pre-training on one task can accelerate training or improve performance on another task, and what mechanism

researcharxiv-cs-lg

2 Oct 2026

Low-Budget Active Learning through Entropic Optimal Transport

arXiv:2610.01199v1 Announce Type: new Abstract: We consider low-budget active learning, which consists of selecting a limited number of points, the coreset, such that a model can be trained to high ac

MaPa: Text-driven Photorealistic Material Painting for 3D Shapes

arXiv:2404.17569v4 Announce Type: replace Abstract: This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to gene

Mathematical Transfer in LLMs Follows Reasoning Approach More Than Topic

arXiv:2610.00331v1 Announce Type: new Abstract: When selecting mathematical training data for LLMs, a natural organizing principle is topic: probability examples for probability targets. An alternativ

MatrixReward: Reward from Rubric Matrix for Open-Ended Generation

arXiv:2610.00389v1 Announce Type: cross Abstract: Open-ended query generation lacks standard answers, thus necessitating an effective reward mechanism. Pointwise scoring rubrics provide limited inform

MEGA: Object-Level Mesh Extraction from 3D Gaussian Splatting via Spatial Visual Distillation

arXiv:2610.01707v1 Announce Type: new Abstract: Mesh extraction from 3D Gaussian Splatting (3DGS) aims to endow 3D Gaussians with accurate geometric structures, enabling explicit and precise 3D occupa

MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI

arXiv:2610.02136v1 Announce Type: cross Abstract: Unsupervised anomaly detection (UAD) methods for brain MRI are ranked by a single score, yet that score rests on choices that are rarely reported: how

Misalignment of Low-Loss Regions Causes Grokking

arXiv:2610.00620v1 Announce Type: cross Abstract: Grokking refers to the delayed emergence of validation-set generalization after a model has already overfit the training set. Although first observed

Model Merging via Data-Free Covariance Estimation

arXiv:2604.01329v2 Announce Type: replace Abstract: Model merging provides a way of cheaply combining individual models to produce a model that inherits each individual's capabilities. While some merg

MoLE: Mixture of Latent Experts for Complementary Visual Reasoning

arXiv:2610.01917v1 Announce Type: cross Abstract: Latent visual reasoning equips vision--language models with continuous intermediate states that can process visual evidence without explicit textual r

Moore, Escher, Penrose: A Conformal Golden Braid

arXiv:2610.02210v1 Announce Type: new Abstract: I don't think I have ever done anything as peculiar in my life. Among other things, it shows a young man looking with interest at a print on the wall of

MOVE: Multimodal Open-world Verification and Expansion for Graph Learning

arXiv:2610.00268v1 Announce Type: new Abstract: Multimodal graph learning faces a fundamental challenge: new classes may emerge after deployment, while models are trained with a fixed label space. Exi

Multi-Behavioral Evolved Substrates Through Neuromodulation and Activation Selection

arXiv:2610.00148v1 Announce Type: cross Abstract: Open-ended artificial life systems must acquire diverse competencies from a single evolving genotype. Biological brains combine neuromodulation, which

Multi-Reference Path Tracking Control for an Agricultural Tractor with Nonlinear Model Predictive Control

arXiv:2610.00057v1 Announce Type: new Abstract: Guiding a tractor along a predefined reference path is a key component of precision agriculture. This study develops a path tracking controller based on

researcharxiv-cs-ro

Muon meets Tamed Langevin: Momentum Preconditioning beyond Convex and gradient-Lipschitz Potentials

arXiv:2610.02158v1 Announce Type: new Abstract: We consider the problem of sampling from Gibbs distributions on matrix spaces whose potential energies are neither convex nor globally gradient-Lipschit

MWOP: Modality-aware Width-wise Operation Pruning for Efficient MLLMs

arXiv:2610.01434v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) incur substantial inference costs when processing long visual-textual sequences. While existing operation com

Neural network-driven domain decomposition for efficient solutions to the Helmholtz equation

arXiv:2511.15445v3 Announce Type: replace-cross Abstract: Accurately simulating wave propagation is crucial in fields such as acoustics, electromagnetism, and seismic analysis. Traditional numerical m

NEUROTOKEN: Joint Source and Directional AAD with Envelope Decoding via Conditional Flow Matching

arXiv:2610.00397v1 Announce Type: new Abstract: Identifying which speaker a listener is attending to in a noisy room -- the cocktail-party problem -- is the missing ingredient for next-generation hear

Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation

arXiv:2610.00678v1 Announce Type: cross Abstract: Histological whole-slide images (WSIs) are central to computational pathology but pose severe computational challenges due to their extremely high res

Not All Is Lost: Repairing Lossy User Preference States of Personalization Encoders

arXiv:2610.01270v1 Announce Type: new Abstract: Personalization encoders compress evolving interaction histories into preference states used to rank items or condition text generation. A task head ope

OmniMed-Jev: Calibrating LVLM Confidence for Trustworthy Medical Multimodal Decisions via System One

arXiv:2610.00381v1 Announce Type: new Abstract: Medical models are judged not only on correctness, but on whether reported confidence matches actual accuracy. Generalist multimodal medical models have

On Language Drift during RLVR Post-Training

arXiv:2610.02015v1 Announce Type: cross Abstract: Recent advances in LLM reasoning models---driven primarily by the paradigm of post-training via reinforcement learning with verifiable reward (RLVR)--

On-the-fly Weight Generation: A Hypernetwork Proof of Concept on ARC-1D

arXiv:2610.00820v1 Announce Type: cross Abstract: General-purpose models can adapt to many tasks from context, while specialised models can execute individual functions with less capacity. Yet obtaini

One Mastery Threshold Does Not Fit All Knowledge Tracing Models

arXiv:2610.00095v1 Announce Type: new Abstract: Tutoring systems use mastery thresholds to decide when students can stop practicing and advance, but the same numerical threshold can lead to very diffe

Online Generalized-Mean Welfare Maximization: Achieving Near-Optimal Regret from Samples

arXiv:2602.10469v2 Announce Type: replace-cross Abstract: We study online fair allocation of T sequentially arriving items among n agents with heterogeneous preferences, with the objective of maximizi

Ontology-Based Contextual AI Evaluations (OB-CAIE) Methodology

arXiv:2610.00529v1 Announce Type: new Abstract: The ontology-based contextual AI evaluation (OB-CAIE) methodology was developed to address a lack of scientific rigor that arises from unclear testing c

Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AI

arXiv:2610.00682v1 Announce Type: new Abstract: Large language models (LLMs) increasingly underpin scientific AI applications that reason over structured knowledge, from biomedical question answering

Open Vocabulary Word Recognition From Transcribed Bangla Texts

arXiv:2610.01134v1 Announce Type: new Abstract: An optical character recognition (OCR) can scan a paper and extract text using technology, making people's jobs easier. While various OCR systems are av

Optimal Centered Active Excitation in Linear System Identification

arXiv:2604.05518v2 Announce Type: replace-cross Abstract: We propose an active learning algorithm for linear system identification with optimal centered noise excitation. Notably, our algorithm, based

Optimal Momentum Methods for Stochastic Multilevel Compositional Optimization

arXiv:2610.01572v1 Announce Type: cross Abstract: This paper investigates stochastic multi-level optimization where the objective is a nested composition of several smooth non-convex functions. We ass

Optimal Stochastic Bilevel Optimization with First-Order Oracles

arXiv:2610.01843v1 Announce Type: cross Abstract: We study nonconvex--strongly-convex bilevel optimization under a stochastic first-order oracle. We introduce MRT-FD, a single-loop first-order method

Optimal Transport Meets Reinforcement Learning: A Survey

arXiv:2610.01413v1 Announce Type: cross Abstract: Reinforcement learning (RL) algorithms frequently compare probability distributions, such as state visitation distributions induced by policies and ex

OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivots

arXiv:2610.01148v1 Announce Type: new Abstract: Generating compact and geometrically faithful 3D meshes directly from point clouds remains a fundamental challenge. Point clouds are unordered and spars

Outer Diversity of Condorcet Domains

arXiv:2610.00720v1 Announce Type: cross Abstract: A Condorcet domain is a set of rankings over a given candidate set, such that every election that consists only of (an odd number of) votes from the d

PACE: Persona Adaptation through Conversational Elicitation in Human-Robot Interaction

arXiv:2607.15579v3 Announce Type: replace Abstract: Equipping humanoid robots with coherent and adaptable personas is crucial for fostering natural, engaging, and trustworthy human-robot interaction (

researcharxiv-cs-ro

pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows

arXiv:2610.01663v1 Announce Type: new Abstract: Biomolecular therapeutics often start from known sequences and require targeted editing to improve multiple properties while satisfying hard biochemical

Per-Node Activation Function Evolution in Indirectly Encoded Substrates: Solvability, Limits, and Emergent Diversity

arXiv:2610.00149v1 Announce Type: cross Abstract: Biological neurons achieve computational diversity through specialized types: tonic, bursting, adapting, and fast-spiking cells coexist within the sam

PhaseAT: Fourier Phase Adversarial Training for Medical Image Domain Generalization

arXiv:2610.01807v1 Announce Type: new Abstract: Reliable clinical deployment of deep medical image models is hindered by distribution shifts across scanners, sites, and acquisition protocols. Existing

PickMoment: Continuous-Time Single-Image-to-Video via Learning Deblurring and Blur-to-Video

arXiv:2610.01279v1 Announce Type: cross Abstract: Motion blur arises from the temporal integration of a continuous sharp signal over a finite exposure window, yet existing learning-based methods sides

Polylogarithmic Sparsity of Randomly Reweighted NPMLEs for Gaussian Mixtures

arXiv:2610.01088v1 Announce Type: cross Abstract: The nonparametric maximum likelihood estimator (NPMLE) of a Gaussian location mixture maximizes the likelihood over the infinite-dimensional space of

Pooling Helps, Learned Weighting Hurts In-Context: Decomposing Group Attention

arXiv:2610.01831v1 Announce Type: new Abstract: Group attention, introduced by the time series forecasting model Chronos-2, attends over the variates of a group at a fixed patch index and serves both

Port-Hamiltonian Neural Networks for Systems with Multiple Asymptotically Stable Equilibria

arXiv:2610.01356v1 Announce Type: new Abstract: Stable port-Hamiltonian neural networks certify asymptotic stability by construction. Yet, their Hamiltonian is a global Lyapunov function with a single

Posterior sampling by source-space MCMC via prior-based few-step transport maps

arXiv:2610.01034v1 Announce Type: cross Abstract: Bayesian inference increasingly uses informative but implicit priors represented only by samples, such as historical ensembles, simulator outputs, and

Safety

Pre-training interventions, ex post facto: Grafting model beliefs across checkpoints

arXiv:2610.00767v1 Announce Type: cross Abstract: Pre-training interventions are critical to alignment research, since beliefs formed during pre-training shape how a model generalizes from later train

safetyarxiv-cs-ai

Progressive-Resolution Secure Aggregation for Federated Learning

arXiv:2610.00695v1 Announce Type: cross Abstract: Secure aggregation lets a server recover an aggregate of client updates without observing any individual update, but conventional protocols fix the ag

Provable FDR Control for Deep Feature Selection: Deep MLPs and Beyond

arXiv:2512.04696v3 Announce Type: replace-cross Abstract: We develop a flexible feature selection framework based on deep neural networks that approximately controls the false discovery rate (FDR), a

Pushing CPU Speech Synthesis to the Wall: Extreme Inference Tuning under Serverless Architecture and Billing

arXiv:2610.00063v1 Announce Type: cross Abstract: Instance-billed serverless platforms charge for CPU and memory over the lifetime of a warm instance, making idle inference state a direct serving cost