Detecting Data Errors with Statistical Constraints. - Jing Nathan Yan; Oliver Schulte; Jiannan Wang 001; Reynold Cheng (CoRR, 2019)

Silva: Interactively Assessing Machine Learning Fairness Using Causality. - Jing Nathan Yan; Ziwei Gu; Hubert Lin; Jeffrey M. Rzeszotarski (CHI, 2020)

SCODED: Statistical Constraint Oriented Data Error Detection. - Jing Nathan Yan; Oliver Schulte; Mohan Zhang; Jiannan Wang 001; Reynold Cheng (SIGMOD Conference, 2020)

Tessera: Discretizing Data Analysis Workflows on a Task Level. - Jing Nathan Yan; Ziwei Gu; Jeffrey M. Rzeszotarski (CHI, 2021)

DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python. - Jinglin Peng; Weiyuan Wu; Brandon Lockhart; Song Bian 002; Jing Nathan Yan; Linghao Xu; Zhixuan Chi; Jeffrey M. Rzeszotarski; Jiannan Wang 001 (SIGMOD Conference, 2021)

Understanding User Sensemaking in Machine Learning Fairness Assessment Systems. - Ziwei Gu; Jing Nathan Yan; Jeffrey M. Rzeszotarski (WWW, 2021)

Example-based Spatial Search at Scale. - Hanyuan Zhang; Siqiang Luo; Jieming Shi 001; Jing Nathan Yan; Weiwei Sun 008 (ICDE, 2022)

User Interfaces for Exploratory Data Analysis: A Survey of Open-Source and Commercial Tools. - Jinglin Peng; Weiyuan Wu; Jing Nathan Yan; Danrui Qi; Jeffrey M. Rzeszotarski; Jiannan Wang 001 (IEEE Data Eng. Bull., 2022)

TimelineQA: A Benchmark for Question Answering over Timelines. - Wang-Chiew Tan; Jane Dwivedi-Yu; Yuliang Li 001; Lambert Mathias; Marzieh Saeidi; Jing Nathan Yan; Alon Y. Halevy (ACL (Findings), 2023)

Pretraining Without Attention. - Junxiong Wang; Jing Nathan Yan; Albert Gu; Alexander M. Rush (EMNLP (Findings), 2023)

On What Basis? Predicting Text Preference Via Structured Comparative Reasoning. - Jing Nathan Yan; Tianqi Liu 002; Justin T. Chiu; Jiaming Shen; Zhen Qin 001; Yue Yu 001; Yao Zhao; Charu Lakshmanan; Yair Kurzion; Alexander M. Rush; Jialu Liu; Michael Bendersky (CoRR, 2023)

Predicting Text Preference Via Structured Comparative Reasoning. - Jing Nathan Yan; Tianqi Liu 002; Justin T. Chiu; Jiaming Shen; Zhen Qin 001; Yue Yu 001; Charumathi Lakshmanan; Yair Kurzion; Alexander M. Rush; Jialu Liu; Michael Bendersky (ACL (1), 2024)

Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning. - Yue Yu 001; Jiaming Shen; Tianqi Liu 002; Zhen Qin 001; Jing Nathan Yan; Jialu Liu; Chao Zhang 014; Michael Bendersky (ACL (1), 2024)

Diffusion Models Without Attention. - Jing Nathan Yan; Jiatao Gu; Alexander M. Rush (CVPR, 2024)

MambaByte: Token-free Selective State Space Model. - Junxiong Wang; Tushaar Gangavarapu; Jing Nathan Yan; Alexander M. Rush (CoRR, 2024)

A Controlled Study on Long Context Extension and Generalization in LLMs. - Yi Lu; Jing Nathan Yan; Songlin Yang; Justin T. Chiu; Siyu Ren; Fei Yuan 006; Wenting Zhao; Zhiyong Wu 003; Alexander M. Rush (CoRR, 2024)

EG4D: Explicit Generation of 4D Object without Score Distillation. - Qi Sun; Zhiyang Guo; Ziyu Wan; Jing Nathan Yan; Shengming Yin; Wengang Zhou 001; Jing Liao 001; Houqiang Li (ICLR, 2025)

Fairness Practices in Industry: A Case Study in Machine Learning Teams Building Recommender Systems. - Jing Nathan Yan; Junxiong Wang; Jeffrey M. Rzeszotarski; Allison Koenecke (CoRR, 2025)

OverFill: Two-Stage Models for Efficient Language Model Decoding. - Woojeong Kim; Junxiong Wang; Jing Nathan Yan; Mohamed Abdelfattah; Alexander M. Rush (CoRR, 2025)