Fangzheng (Frank) Xu

Gates and Hillman Centers 5418
Language Technology Institute
School of Computer Science
Carnegie Mellon University
5000 Forbes Ave,
Pittsburgh, PA 15213

Email: fangzhex[at]cs.cmu.edu
Frank Xu Bio

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Bio

I am a PhD student at Language Technologies Institute of Carnegie Mellon University, advised by Graham Neubig, working on natural language processing, and supported by IBM Ph.D. Fellowship since Fall 2022. I received my Bachelor's and Master's degree in Computer Science from Shanghai Jiao Tong University in 2016 and 2019, advised by Kenny Q. Zhu.

Research

My current line of work is closely aligned with both natural language and software engineering, and the bridging between the two. The eventual goal is to enable machine learning models to capture the procedural and intent semantics of the natural language commands, to understand the semantics and structures of programming languages, and to bridge the two drastically different domains of languages together, so that users could use natural language to instruct the computers in the future. I put special emphasis on instance-based models such as retrieval augmented models, and natural language to code generation as an important application.

Publications (* indicates equal contribution)

Conference Papers

MCoNaLa: A Benchmark for Code Generation from Multiple Natural Languages.
Zhiruo Wang, Grace Cuenca, Shuyan Zhou, Frank F. Xu, Graham Neubig.
Preprint, 2022 [paper] [code]

A Systematic Evaluation of Large Language Models of Code.
Frank F. Xu, Uri Alon, Graham Neubig, Vincent J Hellendoorn.
In Deep Learning For Code (DL4C) Workshop @ ICLR and The 6th Annual Symposium on Machine Programming (MAPS) @ PLDI, 2022 [paper] [code]

Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval.
Uri Alon, Frank F. Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig.
Preprint, 2022 [paper]

Capturing Structural Locality in Non-parametric Language Models.
Frank F. Xu, Junxian He, Graham Neubig, Vincent J. Hellendoorn.
In International Conference on Learning Representations (ICLR), 2022 [paper]

In-IDE Code Generation from Natural Language: Promise and Challenges.
Frank F. Xu, Bogdan Vasilescu, Graham Neubig.
In ACM Transactions on Software Engineering and Methodology, 2021 [arXiv] (Presented in ICSE'22 Journal First Track)

Learning Structural Edits via Incremental Tree Transformations.
Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig.
In International Conference on Learning Representations (ICLR), 2021 [paper][code]

Data-to-Text Generation with Style Imitation.
Shuai Lin, Wentao Wang, Zichao Yang, Xiaodan Liang, Frank F. Xu, Eric Xing, Zhiting Hu.
In Findings of the Association for Computational Linguistics: EMNLP, 2020 [paper][code]

A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos.
Frank F. Xu, Lei Ji, Botian Shi, Junyi Du, Graham Neubig, Yonatan Bisk, Nan Duan.
In Proceedings of the First International Workshop on Natural Language Processing Beyond Text @ EMNLP, 2020 [paper][code]

Minimally Supervised Categorization of Text with Metadata.
Yu Zhang, Yu Meng, Jiaxin Huang, Frank F. Xu, Xuan Wang, Jiawei Han.
In Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020 [paper][code]

Incorporating External Knowledge through Pre-training for Natural Language to Code Generation.
Frank F. Xu*, Zhengbao Jiang*, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig.
In Proceedings of 58th Annual Meeting of the Association for Computational Linguistics (ACL), 2020 [paper][code]

How Can We Know What Language Models Know?
Zhengbao Jiang*, Frank F. Xu*, Jun Araki, Graham Neubig.
In Transactions of the Association for Computational Linguistics (TACL), 2020 [paper][code]

Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings.
Ahmed El-Kishky, Frank F. Xu, Aston Zhang, and Jiawei Han.
In Proceedings of IEEE International Conference on Big Data, 2019 [paper]

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories.
Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, Jiawei Han.
In Proceedings of IEEE International Conference on Data Mining (ICDM), 2019 [paper] [GitHub]

StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible.
Anhong Guo, Junhan Kong, Michael Rivera, Frank F. Xu, Jeffrey P. Bigham.
In Proceedings of 32nd Annual ACM Symposium on User Interface Software and Technology (UIST), 2019 [video preview] [video] [paper]

AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging.
Bill Y. Lin*, Dong-Ho Lee*, Frank F. Xu, Ouyu Lan, Xiang Ren.
In Proceedings of 57th Annual Meeting of the Association for Computational Linguistics (ACL Demo), 2019 [GitHub] [website] [paper]

Mining Cross-Cultural Differences and Similarities in Social Media.
Frank F. Xu*, Bill Y. Lin*, Kenny Q. Zhu, Seung-won Hwang.
In Proceedings of 56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018 [PDF]

Automatic Extraction of Commonsense LocatedNear Knowledge.
Frank F. Xu*, Bill Y. Lin*, Kenny Q. Zhu.
In Proceedings of 56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018 [PDF]

ExtRA: Extracting Prominent Review Aspects from Customer Feedback.
Zhiyi Luo, Shanshan Huang, Frank F. Xu, Bill Yuchen Lin, Hanyuan Shi, Kenny Zhu.
In Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018 [PDF]

Empower Sequence Labeling with Task-Aware Neural Language Model.
Liyuan Liu, Jingbo Shang, Frank F. Xu, Xiang Ren, Huan Gui, Jian Peng, Jiawei Han.
In Proceedings of Thirty-second AAAI Conference on Artificial Intelligence (AAAI), 2018. [arXiv]

ReQuest: Indirect Supervision for Relation Extraction using Question-Answer Pairs.
Zeqiu Wu, Xiang Ren, Frank F. Xu, Ji Li, Jiawei Han.
In Proceedings of The 11th ACM International Conference on Web Search and Data Mining (WSDM), 2018. [arXiv]

Open Information Extraction with Global Structure Constraints.
Qi Zhu, Xiang Ren, Jingbo Shang, Yu Zhang, Frank F. Xu, Jiawei Han.
In Proceedings of The Web Conference (WWW Poster), 2018. (Best Poster Award Honorable Mention) [PDF]

Entropy-Based Subword Mining with an Application to Word Embeddings.
Ahmed El-Kishky, Frank F. Xu, Aston Zhang, Stephen Macke, Jiawei Han.
In Proceedings of the Second Workshop on Subword/Character LEvel Models (SCLeM) at NAACL, 2018. [PDF]

Mining Cross-Cultural Differences of Named Entities: A Preliminary Study.
Frank F. Xu*, Bill Y. Lin*, Kenny Q. Zhu.
Appeared on First Workshop on Knowledge Base Construction, Reasoning and Mining (KBCOM) at WSDM, 2018. [PDF]

Commonsense LocatedNear Relation Extraction.
Frank F. Xu*, Bill Y. Lin*, Kenny Q. Zhu.
Appeared on 6th Workshop on Automated Knowledge Base Construction (AKBC) at NIPS, 2017. [arXiv]

Multi-channel BiLSTM-CRF Model for Emerging Named Entity Recognition in Social Media.
Frank F. Xu*, Bill Y. Lin*, Zhiyi Luo, Kenny Q. Zhu.
In Proceedings of the 3rd Workshop on Noisy User-generated Text (W-NUT) at EMNLP, 2017. [PDF] (2nd place in the shared task)

Transfer Learning for Traffic Speed Prediction: A Preliminary Study.
Frank F. Xu*, Bill Y. Lin*, Eve Q. Liao, Kenny Q. Zhu
In Proceedings of SmartIoT 2018 Workshop: AI enhanced IoT data processing for Intelligent Applications, at AAAI, 2018 [PDF]

Cross-region Traffic Prediction for China on OpenStreetMap.
Frank F. Xu, Bill Y. Lin, Qi Lu, Yifei Huang and Kenny Q. Zhu.
In Proceedings of the 9th ACM SIGSPATIAL International Workshop on Computational Transportation Science, 2016. [PDF]

Thesis

Indirect Supervision for Information Extraction
Frank F. Xu
Master's Thesis, 2019. [PDF]

Traffic Prediction for Urban Planning
Frank F. Xu
Bachelor's Thesis (Best Thesis Award, Top 1% in SJTU, Top 1 in CSE department), 2016. [PDF][Slides][Poster][Video]


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This page was last updated on Apr. 15, 2021

This page was initially created on May 1, 2016