Papers
Research papers from arXiv and related sources
PonderLM-3: Adaptive Token-Wise Pondering with Differentiable Masking
Test-time scaling has shown that allocating more additional computation at inference can improve generation quality, motivating a natural follow-up question: where should this computation be spent?...
He Li, Feichen Song, Boyi Zeng, Shixiang Song, Zhiqin John Xu, Ziwei He, Zhouhan Lin
CausalWrap: Model-Agnostic Causal Constraint Wrappers for Tabular Synthetic Data
Tabular synthetic data generators are typically trained to match observational distributions, which can yield high conventional utility (e.g., column correlations, predictive accuracy) yet poor pre...
Amir Asiaee, Zhuohui J. Liang, Chao Yan
Kruskal-EDS: Edge Dynamic Stratification
We introduce Kruskal-EDS (Edge Dynamic Stratification), a distribution-adaptive variant of Kruskal's minimum spanning tree (MST) algorithm that replaces the mandatory $Θ$(m log m) global sort with ...
Yves Mercadier
Wasserstein-based identification of metastable states in time series data via change point detection and segment clustering
Change point detection for time series analysis is a difficult and important problem in applied statistics, for which a variety of approaches have been developed in the past several decades. Here, ...
David Gentile, Joshua Huang, James M. Murphy
Robust White Blood Cell Classification with Stain-Normalized Decoupled Learning and Ensembling
White blood cell (WBC) classification is fundamental for hematology applications such as infection assessment, leukemia screening, and treatment monitoring. However, real-world WBC datasets present...
Luu Le, Hoang-Loc Cao, Ha-Hieu Pham, Thanh-Huy Nguyen, Ulas Bagci
CoVAE: correlated multimodal generative modeling
Multimodal Variational Autoencoders have emerged as a popular tool to extract effective representations from rich multimodal data. However, such models rely on fusion strategies in latent space tha...
Federico Caretti, Guido Sanguinetti
PreSight: Preoperative Outcome Prediction for Parkinson's Disease via Region-Prior Morphometry and Patient-Specific Weighting
Preoperative improvement rate prediction for Parkinson's disease surgery is clinically important yet difficult because imaging signals are subtle and patients are heterogeneous. We address this set...
Yand Wang, Chen Zhang, Lanyun Zhu, Yixin Chen, Qunbo Wang, Yutong Bai, Jurgen Germann, Yinghong W...
When Numbers Tell Half the Story: Human-Metric Alignment in Topic Model Evaluation
Topic models uncover latent thematic structures in text corpora, yet evaluating their quality remains challenging, particularly in specialized domains. Existing methods often rely on automated metr...
Thibault Prouteau, Francis Lareau, Nicolas Dugué, Jean-Charles Lamirel, Christophe Malaterre
A Simulation Study to Compare Inferential Properties when Modelling Ordinal Outcomes: The Case for the (Plain but Robust) Proportional Odds Model
Ordinal measurements are common outcomes in studies within psychology, as well as in the social and behavioral sciences. Choosing an appropriate regression model for analysing such data poses a dif...
Stefan Inerle, Markus Pauly, Moritz Berger
CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification
Developing multi-turn interactive tool-use agents is challenging because real-world user needs are often complex and ambiguous, yet agents must execute deterministic actions to satisfy them. To add...
Jinpeng Chen, Cheng Gong, Hanbo Li, Ziru Liu, Zichen Tian, Xinyu Fu, Shi Wu, Chenyang Zhang, Wu Z...
AdaPonderLM: Gated Pondering Language Models with Token-Wise Adaptive Depth
Test-time scaling via recurrent/iterative Transformers enables large language models to spend more computation at inference, but most pretrained recurrent LMs run a fixed number of iterations, wast...
Shixiang Song, He Li, Zitong Wang, Boyi Zeng, Feichen Song, Yixuan Wang, Zhiqin John Xu, Ziwei He...
Exploring $\widetilde{R}_2$ Leptoquarks and Majorana Neutrinos via same-sign dimuons at the HL-LHC
We study the phenomenology of scalar leptoquark (sLQ) $\widetilde{R}_2$ coupled to right-handed neutrinos (RHNs) at the High-Luminosity Large Hadron Collider (HL-LHC), focusing on signatures that d...
Subham Saha, Arvind Bhaskar, Manimala Mitra
Dynamic Connectivity and Local Frequency Strength under Stochastic Variations
This paper introduces a novel metric, termed the Generalized Fiedler Vector (GFV), to evaluate the \textit{dynamic connectivity} in power systems. The proposed metric leverages the network connecti...
Bruno Pinheiro, Daniel Dotta
B-fields And dust in interstelLar fiLAments using Dust POLarization (BALLAD-POL): VI. Grain alignment mechanisms in the massive quiescent filament G16.96+0.27 using dust polarization observations from JCMT/POL-2
Dust polarization induced by aligned non-spherical grains acts as an important tool to trace the magnetic field (B-field) morphologies and strengths in molecular clouds and constrain grain properti...
Saikhom Pravash, Thiem Hoang, Archana Soam, Qi-Lao Gu, Tie Liu, Pham Ngoc Diep, Le Ngoc Tram, Ngu...
Generative Visual Chain-of-Thought for Image Editing
Existing image editing methods struggle to perceive where to edit, especially under complex scenes and nuanced spatial instructions. To address this issue, we propose Generative Visual Chain-of-Tho...
Zijin Yin, Tiankai Hang, Yiji Cheng, Shiyi Zhang, Runze He, Yu Xu, Chunyu Wang, Bing Li, Zheng Ch...
Asymptotic Analysis of Shallow Water Moment Equations
The Shallow Water Moment Equations (SWME) are an extension of the Shallow Water Equations (SWE) for improved modelling of free-surface flows. In contrast to the SWE, the SWME incorporate vertical v...
Mieke Daemen, Julio Careaga, Zhenning Cai, Julian Koellermeier
Growth factor in teleparallel Gauss-Bonnet gravity
Teleparallel gravity offers a competing geometric framework on which to build cosmological models. The Gauss-Bonnet invariant captures key aspects of the underlying geometry that has been shown to ...
Shivam Kumar Mishra, Jackson Levi Said, B. Mishra
Predicting the Peak Energy of Swift Gamma-Ray Bursts Using Supervised Machine Learning
Gamma-ray bursts (GRBs) are among the most energetic explosive phenomena in the universe, and their peak energy ($E_{\rm p}$) is a key physical quantity for understanding the prompt emission mechan...
Wan-Peng Sun, Si-Yuan Zhu, Da-Ling Ma, Fu-Wen Zhang
Absolute scintillator light yield correction for SiPIN readout via Transfer Matrix Method and Geant4 optical simulation
Precise measurement of the absolute light yield (LY) of scintillators has long been limited by systematic effects inherent in realistic readout geometries. Large-angle incidence, multiple reflectio...
Ge Ma, Zhiyang Yuan, Chencheng Feng, Zirui Yang, Zhenwei Yang, Ming Zeng
Decoupling of topology and texture in optical skyrmions under turbulence
Topological structure is widely invoked as a route to disorder-resilient photonic states, yet whether it protects locally resolved field structure under realistic disorder has not been established....
D. G. Pires, N. M. Litchinitser