Dake Zhang

Hi, I am a PhD student in Computer Science at the University of Waterloo, advised by Professor Mark D. Smucker, and a member of the Data Systems Group.

My current research focuses on Information Retrieval, Natural Language Processing, and Artificial Intelligence, with an aim of helping Internet users evaluate the trustworthiness of online information more effectively and efficiently. My work also benefits from close collaborations with Professor Charles L. A. Clarke and Professor Robin Cohen, whose expertise helps inform and enhance my independent research.

Previously, I received my Master’s degree in Computer Science from the University of Waterloo and my Bachelor’s degree in Software Engineering from Wuhan University.

News

Oct 31, 2024	Our proposal for the Trust in News Track was accepted by TREC 2025. This track is a continuation of the previous Lateral Reading Track, aiming to help Internet users better evaluate online news.
Oct 18, 2024	I am co-organizing Eval4RAG: Workshop on Evaluation of RAG Systems at ECIR 2025. Look forward to presentations and discussions on how to better evaluate RAG systems.
Oct 20, 2023	Our proposal for the Lateral Reading Track was accepted by TREC 2024. This track aims to foster the development of systems to support news readers in performing the tested practice of lateral reading.

Selected Publications

Unrefereed
ReadProbe: A Demo of Retrieval-Enhanced Large Language Models to Support Lateral Reading

Dake Zhang, and Ronak Pradeep

In arXiv preprint arXiv:2306.07875, 2023

Hackathon Winner Bib PDF Code

First place at the 2023 Canadian #AI Misinformation Hackathon hosted by TMU Social Media Lab: https://socialmedialab.ca/events/hackathon/
@inproceedings{zhang2023readprobe, title = {ReadProbe: A Demo of Retrieval-Enhanced Large Language Models to Support Lateral Reading}, author = {Zhang, Dake and Pradeep, Ronak}, booktitle = {arXiv preprint arXiv:2306.07875}, year = {2023} }

Refereed Short

Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search

Dake Zhang, Amir Vakili Tahami, Mustafa Abualsaud, and Mark D. Smucker

In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

Bib PDF Code

@inproceedings{zhang2022learning,
  title = {Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search},
  author = {Zhang, Dake and Tahami, Amir Vakili and Abualsaud, Mustafa and Smucker, Mark D.},
  booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year = {2022}
}