Yuan-Sen Ting

According to our database, Yuan-Sen Ting authored at least 32 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI.

Xiaosheng Zhao, Yuan-Sen Ting, Rosemary F. G. Wyse, Alexander S. Szalay, Yang Huang, László Dobos, Tamás Budavári, Viska Wei

CoRR, February, 2026

Predicting New Concept-Object Associations in Astronomy by Mining the Literature.

Jinchu Li, Yuan-Sen Ting, Alberto Accomazzi, Tirthankar Ghosal, Nesar Ramachandra

CoRR, February, 2026

What Understanding Means in AI-Laden Astronomy.

Yuan-Sen Ting, André Curtis-Trudel, Siyu Yao

CoRR, January, 2026

2025

Why Machine Learning Models Systematically Underestimate Extreme Values II: How to Fix It with LatentNN.

Yuan-Sen Ting

CoRR, December, 2025

Deep Learning in Astrophysics.

Yuan-Sen Ting

CoRR, October, 2025

Large Language Models Achieve Gold Medal Performance at the International Olympiad on Astronomy & Astrophysics (IOAA).

Lucas Carrit Delgado Pinheiro, Ziru Chen, Bruno Caixeta Piazza, Ness B. Shroff, Yingbin Liang, Yuan-Sen Ting, Huan Sun

CoRR, October, 2025

Interpreting deep learning-based stellar mass estimation via causal analysis and mutual information decomposition.

Wei Zhang, Qiufan Lin, Yuan-Sen Ting, Shupei Chen, Hengxin Ruan, Song Li, Yifan Wang

CoRR, September, 2025

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).

Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella S. R. Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang

CoRR, September, 2025

SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars.

Xiaosheng Zhao, Yang Huang, Guirong Xue, Xiao Kong, Jifeng Liu, Xiaoyu Tang, Timothy C. Beers, Yuan-Sen Ting, A-Li Luo

CoRR, July, 2025

Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation.

Chenrui Ma, Zechang Sun, Tao Jing, Zheng Cai, Yuan-Sen Ting, Song Huang, Mingyu Li

CoRR, June, 2025

Statistical Machine Learning for Astronomy - A Textbook.

Yuan-Sen Ting

CoRR, June, 2025

AstroMLab 4: Benchmark-Topping Performance in Astronomy Q&A with a 70B-Parameter Domain-Specialized Reasoning Model.

Tijmen de Haan, Yuan-Sen Ting, Tirthankar Ghosal, Tuan Dung Nguyen, Alberto Accomazzi, Emily Herron, Vanessa Lama, Rui Pan, Azton Wells, Nesar Ramachandra

CoRR, May, 2025

Scaling Laws for Emulation of Stellar Spectra.

Tomasz Rózanski, Yuan-Sen Ting

CoRR, March, 2025

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants.

Franck Cappello, Sandeep Madireddy, Robert Underwood, Neil Getty, Nicholas Lee-Ping Chia, Nesar Ramachandra, Josh Nguyen, Murat Keçeli, Tanwi Mallick, Zilinghan Li, Marieme Ngom, Chenhui Zhang, Angel Yanguas-Gil, Evan R. Antoniuk, Bhavya Kailkhura, Minyang Tian, Yufeng Du, Yuan-Sen Ting, Azton Wells, Bogdan Nicolae, Avinash Maurya, M. Mustafa Rafique, Eliu A. Huerta, Bo Li, Ian T. Foster, Rick Stevens

CoRR, February, 2025

AstroMLab 1: Who wins astronomy jeopardy!?

Yuan-Sen Ting, Tuan Dung Nguyen, Tirthankar Ghosal, Rui Pan, Hardik Arora, Zechang Sun, Tijmen de Haan, Nesar Ramachandra, Azton Wells, Sandeep Madireddy, Alberto Accomazzi

Astron. Comput., 2025

Effective Training Data Synthesis for Improving MLLM Chart Understanding.

Yuwei Yang, Zeyu Zhang, Yunzhong Hou, Zhuowan Li, Gaowen Liu, Ali Payani, Yuan-Sen Ting, Liang Zheng

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

2024

CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimation.

Qiufan Lin, Hengxin Ruan, Dominique Fouchez, Shupei Chen, Rui Li, Paulo Montero-Camacho, Nicola R. Napolitano, Yuan-Sen Ting, Wei Zhang

CoRR, 2024

pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy.

Kartheik Iyer, Mikaeel Yunus, Charles O'Neill, Christine Ye, Alina Hyk, Kiera McCormick, Ioana Ciuca, John F. Wu, Alberto Accomazzi, Simone Astarita, Rishabh Chakrabarty, Jesse Cranney, Anjalie Field, Tirthankar Ghosal, Michele Ginolfi, Marc Huertas-Company, Maja Jablonska, Sandor Kruk, Huiling Liu, Gabriel Marchidan, Rohit Mistry, Jill P. Naiman, Joshua E. G. Peek, Mugdha Polimera, Sergio J. Rodríguez Méndez, Kevin Schawinski, Sanjib Sharma, Michael J. Smith, Yuan-Sen Ting, Mike Walmsley

CoRR, 2024

Knowledge Graph in Astronomical Research with Large Language Models: Quantifying Driving Forces in Interdisciplinary Scientific Discovery.

Zechang Sun, Yuan-Sen Ting, Yaobo Liang, Nan Duan, Song Huang, Zheng Cai

CoRR, 2024

The Scaling Law in Stellar Light Curves.

Jiashu Pan, Yuan-Sen Ting, Yang Huang, Jie Yu, Ji-Feng Liu

CoRR, 2024

AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets.

Ernest Perkowski, Rui Pan, Tuan Dung Nguyen, Yuan-Sen Ting, Sandor Kruk, Tong Zhang, Charlie O'Neill, Maja Jablonska, Zechang Sun, Michael J. Smith, Huiling Liu, Kevin Schawinski, Kartheik Iyer, Ioana Ciuca, UniverseTBD

CoRR, 2024

AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy.

Rui Pan, Tuan Dung Nguyen, Hardik Arora, Alberto Accomazzi, Tirthankar Ghosal, Yuan-Sen Ting

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

2023

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers.

Daniela Huppenkothen, Michelle Ntampaka, M. Ho, M. Fouesneau, Brian Nord, Joshua E. G. Peek, Mike Walmsley, John F. Wu, Camille Avestruz, Tobias Buck, M. Brescia, D. P. Finkbeiner, Andy D. Goulding, Tomasz Kacprzak, Peter Melchior, M. Pasquato, Nesar Ramachandra, Yuan-Sen Ting, G. van de Ven, S. Villar, V. A. Villar, Elad Zinger

CoRR, 2023

Astroconformer: The Prospects of Analyzing Stellar Light Curves with Transformer-Based Deep Learning Models.

Jiashu Pan, Yuan-Sen Ting, Jie Yu

CoRR, 2023

AstroLLaMA: Towards Specialized Foundation Models in Astronomy.

Tuan Dung Nguyen, Yuan-Sen Ting, Ioana Ciuca, Charlie O'Neill, Zechang Sun, Maja Jablonska, Sandor Kruk, Ernest Perkowski, Jack W. Miller, Jason Li, Josh Peek, Kartheik Iyer, Tomasz Rózanski, Pranav Khetarpal, Sharaf Zaman, David Brodrick, Sergio J. Rodríguez Méndez, Thang D. Bui, Alyssa Goodman, Alberto Accomazzi, Jill P. Naiman, Jesse Cranney, Kevin Schawinski, UniverseTBD

CoRR, 2023

Adversarial Fine-Tuning of Language Models: An Iterative Optimisation Approach for the Generation and Detection of Problematic Content.

Charles O'Neill, Jack W. Miller, Ioana Ciuca, Yuan-Sen Ting, Thang D. Bui

CoRR, 2023

Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation.

Charles O'Neill, Yuan-Sen Ting, Ioana Ciuca, Jack W. Miller, Thang D. Bui

CoRR, 2023

Harnessing the Power of Adversarial Prompting and Large Language Models for Robust Hypothesis Generation in Astronomy.

Ioana Ciuca, Yuan-Sen Ting, Sandor Kruk, Kartheik Iyer

CoRR, 2023

Galactic ChitChat: Using Large Language Models to Converse with Astronomy Literature.

Ioana Ciuca, Yuan-Sen Ting

CoRR, 2023

2022

Astroconformer: Inferring Surface Gravity of Stars from Stellar Light Curves with Transformer.

Jiashu Pan, Yuan-Sen Ting, Jie Yu

CoRR, 2022

2021

Dataset used in "Uncertainty-Aware Learning for Improvements in Image Quality of the Canada-France-Hawaii Telescope" (https://arxiv.org/abs/2107.00048).

Sankalp Gilda, Stark C. Draper, Sebastien Fabbro, William Mahoney, Simon Prunet, Kanoa Withington, Matthew Wilson, Yuan-Sen Ting, Andrew Sheinis

Dataset, August, 2021

Uncertainty-Aware Learning for Improvements in Image Quality of the Canada-France-Hawaii Telescope.

Sankalp Gilda, Stark C. Draper, Sebastien Fabbro, William Mahoney, Simon Prunet, Kanoa Withington, Matthew Wilson, Yuan-Sen Ting, Andrew Sheinis

CoRR, 2021