Sheng-Chieh (Jack) Lin


Ph.D. Student, University of Waterloo

About Me

Hi, I’m the Ph.D. student supervised by Jimmy Lin in the David R. Cheriton School of Computer Science at the University of Waterloo starting from 2020. My research interests are dense retrieval for text search and its application to conversational search. I’m interested in building a simple yet effective approach to information retrieval.

Previously, I was a senior engineer at TSMC and working on improving CMOS image sensors through data analysis and knowledge of semiconductor. This experience shapes my research philosophy: human prior knowledge is the key to telling the story behind data and solving problems.


Densifying Sparse Representations for Passage Retrieval by Representational Slicing.
Sheng-Chieh Lin, Jimmy Lin. arXiv:2112.04666, Dec 2021.

Contextualized Query Embeddings for Conversational Search.
Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin.
EMNLP, Nov 2021. [code][Pyserini][arxiv]

In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval.
Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin.
ACL workshop on Representation Learning for NLP (RepL4NLP), Aug 2021. [code][Pyserini][arxiv]

Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting.
Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira, Ming-Feng Tsai, Chuan-Ju Wang, and Jimmy Lin.
TOIS, Aug 2021. [code][arxiv]

Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling.
Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury.
SIGIR, July 2021.

Chatty Goose: A Python Framework for Conversational Search.
Edwin Zhang, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, Rodrigo Nogueira, and Jimmy Lin.
SIGIR Demonstrations, July 2021. [code]

Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations.
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira.
SIGIR Resource Papers, July 2021.

Designing Templates for Eliciting Commonsense Knowledge from Pretrained Sequence-to-Sequence Models.
Jheng-Hong Yang, Sheng-Chieh Lin, Rodrigo Nogueira, Ming-Feng Tsai, Chuan-Ju Wang, and Jimmy Lin.
COLING, December 2020. [arxiv]

Personalized TV Recommendation: Fusing User Behavior and Preferences.
Sheng-Chieh Lin, Ting-Wei Lin, Jing-Kai Lou, Ming-Feng Tsai, Chuan-Ju Wang.
arXiv:2104.08707, August 2020.

Negative-Aware Collaborative Filtering.
Sheng-Chieh Lin, Yu-Neng Chuang, Sheng-Fang Yang, Ming-Feng Tsai and Chuan-Ju Wang.
RecSys (Late-Breaking Results), September 2019.