Xi Ye
叢曦

Ph.D. Student, Computer Science
The University of Texas at Austin

xiye [at] cs.utexas.edu   xiye17   scholar   xiye_nlp

I am a final-year Ph.D. student in the Department of Computer Science at UT Austin, advised by Greg Durrett. I am also a part of the TAUR lab (Text Analysis, Understanding, and Reasoning).

My research focuses on Natural Language Processing and the interpretability of NLP models in particular. Specifically, I am interested in leveraging explanations to steer and calibrate language models for complex textual reasoning tasks. I also work on semantic parsing and program synthesis.

Prior to joining UT Austin, I obtained my Bachelor's degree from the School of Software, Tsinghua University, where I worked with Prof. Shixia Liu on Visual Analysis and Machine Learning.

πŸ“£ I am on academic job market this academic year (2023-2024).    [CV]   [Research Statement]
πŸ“£ [06/2024] Our tutorial Explanation in the Era of Large Language Models is accepted to appear @ NAACL 2024
πŸ“£ [08/2024] I'll co-organize the Natural Language Reasoning and Structured Explanations Workshop @ ACL 2024. Please consider submitting to our workshop.

Publications

Effective Large Language Model Adaptation for Improved Grounding and Citation Generation

Xi Ye, Ruoxi Sun, Sercan Γ–. Arik, and Tomas Pfister. NAACL 2024.

Crafting In-context Examples according to LMs' Parametric Knowledge

Yoonsang Lee*, Pranav Atreya*, Xi Ye, and Eunsol Choi. Findings of NAACL 2024.

MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning website

Zayne Sprague, Xi Ye, Kaj Bostrom, Swarat Chaudhuri, and Greg Durrett. Proceedings of ICLR 2024 (spotlight).

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting code

Xi Ye, Qiaochu Chen, Isil Dillig, and Greg Durrett. Proceedings of NeurIPS 2023.

Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting code

Xi Ye, and Greg Durrett. Proceedings of EMNLP 2023.

Complementary Explanations for Effective In-Context Learning code

Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Ves Stoyanov, Greg Durrett, and Ramakanth Pasunuru. Findings of ACL, 2023.

EEL: Efficiently Encoding Lattices for Reranking code

Prasann Singhal, Jiacheng Xu, Xi Ye, and Greg Durrett. Proceedings of ACL, 2023.

Assessing Out-of-Domain Language Model Performance from Few Examples

Prasann Singhal*, Jarad Forristal*, Xi Ye, and Greg Durrett. Proceedings of EACL 2023.

The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning code

Xi Ye and Greg Durrett. Proceedings of NeurIPS 2022.

Can Explanations Be Useful for Calibrating Black Box Models? code

Xi Ye and Greg Durrett. Proceedings of ACL 2022.

RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering code

Xi Ye, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou, and Caiming Xiong. Proceedings of ACL 2022.

Diagnosing Ensemble Few-Shot Classifiers demo

Weikai Yang, Xi Ye, Xingxing Zhang, Lanxi Xiao, Jiazhi Xia, Zhongyuan Wang, Jun Zhu, Hanspeter Pfister, and Shixia Liu. Transactions of TVCG 2022.

Connecting Attributions and QA Model Behavior on Realistic Counterfactuals code

Xi Ye, Rohan Nair, and Greg Durrett. Proceedings of EMNLP 2021.

Optimal Neural Program Synthesis from Multimodal Specifications code

Xi Ye, Qiaochu Chen, Isil Dillig, and Greg Durrett. Findings of EMNLP 2021.

Benchmarking Multimodal Regex Synthesis with Complex Structures code data

Xi Ye, Qiaochu Chen, Isil Dillig, and Greg Durrett. Proceedings of ACL 2020.

Sketch-Driven Regular Expression Generation from Natural Language and Examples code

Xi Ye, Qiaochu Chen, Xinyu Wang, Isil Dillig, and Greg Durrett. Transactions of ACL 2020.

Multi-Modal Synthesis of Regular Expressions code

Qiaochu Chen, Xinyu Wang, Xi Ye , Greg Durrett, and Isil Dillig. Proceedings of PLDI 2020

Interactive Correction of Mislabeled Training Data video

Shouxing Xiang*, Xi Ye*, Jiazhi Xia, Jing Wu, Yang Chen, and Shixia Liu. Proceedings of VAST 2019

Talks

[11/2023] On Steering Textual Reasoning with Explanations @ CHAI group, Uchicago.

[10/2023] On Steering Textual Reasoning with Explanations @ Yale NLP Lab, Yale.

[03/2023] On Effective Use of Explanations in Prompting @ Student reading group, UMD. slides

[03/2023] On Effective Use of Explanations in Prompting @ Meetup of MLNLP Community.

[03/2023] On Effective Use of Explanations in Prompting @ DM2Lab, UND.

[11/2022] On Unreliability of Explanations in Prompting @ AI4LIFE group, Harvard.

[06/2022] On Calibration using Explanations @ NeuLab group, CMU.

Service

Area Chair: ACL (24)

Reviewer: ACL (23), ICML (23,24), NeurIPS (22, 23), ICLR (24), EMNLP (22), NAACL (22), ARR (22, 21), CONLL (21, 20), TL4NLP Workshop (22), SUKI Workshop (22), NLP4Prog Workshop (21).

Teaching

TA for CS378: Natural Language Processing (undergraduate). Fall 2022

TA for CS388: Natural Language Processing (graduate). Spring 2021

TA for CS429: Computer Architecture and Organization (undergraduate). Fall 2018, Spring 2019

Experience

Google Cloud AI Research. Research Intern. Summer 2023.

Facebook AI Research. Research Intern. Summer 2022.

Salesforce Research. Research Intern. Summer 2021.