research

Scaling Online Optimal Transport Minibatches for Flow Matching

arXiv:2610.18838v1 Announce Type: cross Abstract: A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically o

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Scaling Vision Transformers Without Training: Prune-and-Merge Token Compression

DGX agent

arXiv:2610.18039v1 Announce Type: new Abstract: Vision Transformers achieve strong performance but incur high computational costs from quadratic token interactions. Training-free token reduction metho

researcharxiv-cs-cv

14 Oct 2026

ScalLoc: Continuous Oblique Thermal UAV Geo-Localization with a 2D Satellite Map

arXiv:2610.14866v1 Announce Type: new Abstract: Cross-modal Thermal Geo-localization (TG) provides an illumination-robust positioning solution for Unmanned Aerial Vehicles (UAVs) in Global Navigation

Screening Collapse under Recursive Synthetic Data

arXiv:2610.15617v1 Announce Type: cross Abstract: Recursive synthetic-data training can degrade a fitted model, but its effects on the variable-screening stage that precedes model fitting are less und

Sea-Net: A Small and Inherently Interpretable Neural Network for Time Series Classification

arXiv:2610.17939v1 Announce Type: cross Abstract: Traditional time-series classification methods often operate as black boxes, providing a class prediction without indicating which time point or time

Selective Inference for Clustering Under Unknown Covariance

arXiv:2610.17458v1 Announce Type: cross Abstract: Unsupervised clustering is widely used to discover underlying group structure, after which researchers often seek to validate these groups via post-ho

SelectTTRL: Representation-Guided Data Selection for Efficient Test-Time Reinforcement Learning

arXiv:2610.16104v1 Announce Type: new Abstract: Test-Time Reinforcement Learning (TTRL) enables large language models to adapt directly on unlabeled test problems by constructing pseudo-labels from mu

Self-improving data synthesis can scale embedding models across domains and tasks

arXiv:2610.14730v1 Announce Type: cross Abstract: Adapting embedding models to new tasks requires training data that reflect task-specific information needs and relevance criteria. However, manual dat

Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images

arXiv:1307.2965v3 Announce Type: replace Abstract: The automatic segmentation of human knee cartilage from 3D MR images is a useful yet challenging task due to the thin sheet structure of the cartilag

Semantic Saliency from Multi-Modal Large Language Model Scene Understanding Maps

arXiv:2610.15467v1 Announce Type: new Abstract: Image-computable low-level image saliency has shaped perceptual psychology and computer science, but is limited by its inability to capture human high-l

Semantically Steerable Image Tokenization

arXiv:2610.15515v1 Announce Type: new Abstract: Adaptive image tokenizers compress an image into a variable number of tokens matched to its complexity, and recent work makes this allocation controllab

SemTree: Judge-Aware Semantic Decision Trees for Inspectable and Repairable Rule Decisions

arXiv:2610.13999v1 Announce Type: new Abstract: Rule decisions such as content moderation, advertising compliance, and eligibility checks combine several conditions, exemptions, and missing-informatio

Sensor-Aware Joint Data Fusion and State Estimation under Sparse Multi-rate Distribution Grid Sensing

arXiv:2610.15156v1 Announce Type: new Abstract: Distribution-system state estimation is a growing necessity for the modern power grid as the addition of local storage and generation add system complex

Sequence Composition in EHR Foundation Model Pretraining

arXiv:2610.16878v1 Announce Type: new Abstract: Autoregressive electronic health record (EHR) foundation models predict the next event token in patient trajectories: sequences of structured medical ev

SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization

arXiv:2603.08185v2 Announce Type: replace Abstract: Post-training quantization (PTQ) has emerged as a prevailing technique for deploying large language models (LLMs) efficiently in terms of both memor

Shared-Control Teleoperation of Omnidirectional Aerial Robots for Continuous Valve Rotation

arXiv:2610.14478v1 Announce Type: new Abstract: Omnidirectional aerial robots offer full 6-DoF independent control over position and orientation, making them popular for aerial manipulation. Although

researcharxiv-cs-ro

SharedSAE: a unified sparse dictionary across u-net blocks and denoising time for diffusion models

arXiv:2610.13997v1 Announce Type: new Abstract: Concept representations in diffusion models drift across network depth and denoising time, yet existing sparse autoencoders offer only per-block or per-

Sharper Frames, Worse Rooms: Viewpoint Coverage Dominates Image Quality in Feed-Forward 3D Reconstruction

arXiv:2610.15854v1 Announce Type: new Abstract: Grounded spatial reasoning about indoor scenes rests on a geometric reconstruction that the multimodal system does not itself produce. Feed-forward mult

Signature-Kernel One-Class Learning with Manifold Regularisation for Multivariate Time Series Anomaly Detection

arXiv:2507.23449v3 Announce Type: replace Abstract: One-class learning is an effective methodology for time series anomaly detection, yet kernel one-class approaches often compare sequences in a point

Sim4RAD: A MATLAB Toolkit for Design-Phase Sizing, Actuator Selection and URDF-Model Verification of Serial Robotic Arms

arXiv:2610.17534v1 Announce Type: new Abstract: Actuator sizing is an early and consequential decision: joint torque and velocity specifications fix the motors, gearboxes and brakes before any CAD mod

researcharxiv-cs-ro

SIRNET: Causal Adaptation of Pretrained Embeddings for Semiparametric Treatment-Effect Estimation Under Surrogacy

arXiv:2610.14011v1 Announce Type: new Abstract: Modern experiments increasingly produce rich post-treatment objects---such as text, images, and video---that may provide early surrogate signals for out

Soft MPCritic: Value-Based Reinforcement Learning for Non-Differentiable Predictive Control

arXiv:2604.01477v2 Announce Type: replace Abstract: Reinforcement learning (RL) and model predictive control (MPC) offer complementary strengths, yet existing MPC-RL frameworks commonly rely on gradie

Softmax-Free Attention in Spiking Transformers as the Zero-Temperature Limit of Two-Level Systems

arXiv:2610.15968v1 Announce Type: new Abstract: Spiking Transformers achieve energy efficiency by discarding softmax normalization in favor of thresholded, binary attention. However, this removal brea

SoK: Rethinking Membership Inference in Tabular Machine Learning

arXiv:2610.18486v1 Announce Type: new Abstract: Membership Inference Attacks (MIAs) are currently the dominant approach to evaluating privacy in machine learning applications. Despite their significan

Solvating machine-learning interatomic potentials for solution-phase chemistry

arXiv:2610.17226v1 Announce Type: cross Abstract: Most machine-learning interatomic potentials (MLIPs) are trained on gas-phase data, which limits their use for chemistry in solution. Here, we introdu

SPARE: Shared Perception and Adaptive Retrieval of Evidence for Streaming Video Understanding

arXiv:2610.14671v1 Announce Type: new Abstract: Streaming video understanding requires answering questions from the observed video, with evidence drawn from recent observations or earlier events. Hist

Sparse All-Layer Connector for Domain Generalised Semantic Segmentation

arXiv:2610.15660v1 Announce Type: new Abstract: Domain generalised semantic segmentation (DGSS) has recently benefited from combining multiple foundation models, such as vision-language and vision fou

Sparsity Saves Compute, Not Samples: Oracle Inequalities for Dense and Sparse Mixture of Experts

arXiv:2610.15039v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models combine specialized experts through an input-dependent routing mechanism, and their sparse variants underpin many modern

Spatiotemporal Recognition of Abdominal Wall Layers During Optical Trocar Entry

arXiv:2610.14512v1 Announce Type: new Abstract: Objective. To evaluate whether spatial context and temporal modeling improve tissue recognition during optical trocar entry, where multiple abdominal-wa

Spectral Considerations on Unsupervised Time-domain EEG Representation Learning with Deep Networks

arXiv:2610.16264v1 Announce Type: new Abstract: Electroencephalography (EEG) is a non-invasive, scalable source of quantitative biomarkers for the early diagnosis of brain disorders, and deep represen

Spectral-Driven Adaptive-Rank Optimizer for Large Language Model Reinforcement Learning with Verifiable Rewards

arXiv:2610.16533v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is reshaping how large language models (LLMs) acquire reasoning capabilities, yet the optimizers

Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary

arXiv:2302.00985v3 Announce Type: replace-cross Abstract: We consider online scheduling on unrelated (heterogeneous) machines in a speed-oblivious setting, where an algorithm is unaware of the exact j

SPLICE: Sparse Physics Library Identification and Compositional Expansion

arXiv:2610.17029v1 Announce Type: new Abstract: Neural operator splitting composes a library of neural operators, one per physical mechanism, into zero-shot simulators of new equations. Existing appro

Stable-Plastic Subspace Construction for Differentially Private Continual LoRA

arXiv:2610.17904v1 Announce Type: new Abstract: Continual learning (CL) adapts pretrained models to a sequence of tasks while retaining knowledge acquired from earlier tasks. When task data are sensit

Statistical Downscaling of Daily Precipitation from ERA5 Atmospheric Fields to IMERG over West Africa

arXiv:2610.16816v1 Announce Type: cross Abstract: Global reanalyses are too coarse to resolve the convective systems that produce most West African monsoon rainfall. In this work, we use U-Net based a

Statistical Vignettes on the Grokking Phenomenon

arXiv:2610.18811v1 Announce Type: new Abstract: In this work, we study grokking in a simple, analytically tractable setting whose rich phenomenology allows us to disentangle the effects of initializat

Steering the Fidelity in State Preparation on Noisy Bosonic Systems with Risk-Seeking Optimization

arXiv:2610.18495v1 Announce Type: cross Abstract: In order to execute quantum algorithms on bosonic quantum computers, it is necessary to encode their inputs into a desired target quantum state, with

StimFlow: Synthesizing Brain Activity from Images via Stimulus-conditioned Flow Matching

arXiv:2610.15341v1 Announce Type: new Abstract: The inherent variability of fMRI responses across trials encourages a generative view of the stimulus-to-response mapping. Prior generative encoders oft

Structure-preserving fidelity diagnostics for partial differential equations

arXiv:2610.17483v1 Announce Type: new Abstract: Machine learning surrogates of partial differential equations (PDEs) are commonly trained on data generated by numerical solvers. Therefore, the trainin

StructZO: Structured Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning

arXiv:2610.16451v1 Announce Type: new Abstract: Fine-tuning large language models at scale is increasingly limited by the memory cost of backpropagation. Zeroth-Order (ZO) optimizers reduce this burde

Surface Reconstruction from Range Scans Under Visibility Constraints

arXiv:2610.18005v1 Announce Type: new Abstract: Surface reconstruction from range scans is challenging in the presence of noise and outliers, as fidelity to observations must be balanced against sensi

SurgCast: Action-Conditioned Future Skeletons for Controllable Surgical World Models

arXiv:2610.15645v1 Announce Type: new Abstract: Surgical world models must turn prospective robot actions into visually faithful, structurally consistent instrument motion. We introduce SurgCast, whic

SWORD: Scene-Grounded Wasserstein Object-Relation Distance for 3D Scene Graph Prediction

arXiv:2610.17692v1 Announce Type: new Abstract: 3D scene graph prediction is commonly optimized with object-node and relation-edge classification losses. These objectives encourage exact object and re

TabGift: A Context-Efficient Foundation Model for Tabular Data Generation

arXiv:2610.16990v1 Announce Type: new Abstract: Tabular data generation aims to synthesize realistic samples from limited observations while faithfully capturing the underlying data distribution. Tabu

TableVision: Recovering Verified Structure from Historical Tables

arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and

TAG: Calibrating SAM3 for Universal Image Segmentation without Dense Supervision

arXiv:2610.14651v1 Announce Type: new Abstract: The recent Segment Anything Model 3 (SAM3) extends powerful promptable segmentation from spatial cues to concepts, raising the prospect of a single foun

TagBO: LLM-Driven Task-Aware Graph Bayesian Optimization for Scientific Discovery

arXiv:2610.14626v1 Announce Type: new Abstract: Mixed-variable optimization in scientific discovery often requires exploring large combinatorial spaces under costly experimental evaluations, making sa

Taming Nonconvexity with Epigraph Lifting

arXiv:2610.16429v1 Announce Type: cross Abstract: We consider inverse problems regularized by a trained neural network with convex activations and unrestricted weights. The resulting optimization prob