Ronak Pradeep
Hi! I am a PhD student in the David R. Cheriton School of Computer Science at the University of Waterloo, advised by Jimmy Lin. The past few months, I've been working on LLMs (and that sort of things) at Yupp AI. During my PhD, I've also had the chance to work at Google and Apple.
Previously, I completed my undergraduate studies at the University of Waterloo, where I majored in Computer Science and Combinatorics and Optimization. During my undergrad, I've had the chance to intern at Quebec Artificial Intelligence Institute (Mila), ContextLogic, and RBC Research.
Research
My research interests lie at the intersection of Information Retrieval and Natural Language Processing. More specifically, I'm interested in tasks such as Open Domain Question Answering, Fact Verification, and Document Ranking. In recent months, I have also been investigating the memory component of Large Language Models and the interplay between the inherent reasoning and memory modules, entangled in a single LLM or otherwise. I look forward to contributing to the next generation of reasoners capable of working with a constantly evolving ocean of both structured and unstructured data. Some of my earlier work explores how to build neural search systems that promote correct and reliable information and work well in low-resource domains such as biomedical texts.
Updates
We have fives papers accepted at SIGIR 2025! See you all in Padova!
We had a successful first year of the TREC RAG 2024 Track with many submissions! Looking forward to Y2.
Organizing the TREC RAG 2024 Track! Do submit your systems :))
We introduced RankZephyr which garnered great community engagement!
I'm excited to visit Singapore for EMNLP 2023 to present our work "How Does Generative Retrieval Scale to Millions of Passages?"
I will be leading the TREC 2024 Retrieval-Augmented Generation Track! More information coming soon!
We introduced RankVicuna, the first zero-shot listwise reranker that leverages open-source LLMs!
Papers
[39] RankLLM: A Python Package for Reranking with LLMs
Sahel Sharifymoghaddam, Ronak Pradeep, Andre Slavescu, Ryan Nguyen, Andrew Xu, Zijian Chen, Yilin Zhang, Yidi Chen, Jasper Xian, Jimmy Lin
[38] Gosling Grows Up: Retrieval with Learned Dense and Sparse Representations Using Anserini
Jimmy Lin, Arthur Haonan Chen, Carlos Lassance, Xueguang Ma, Ronak Pradeep, Tommaso Teofili, Jasper Xian, Jheng-Hong Yang, Brayden Zhong, Vincent Zhong
[37] Support Evaluation for the TREC 2024 RAG Track: Comparing Human versus LLM Judges
Nandan Thakur, Ronak Pradeep, Shivani Upadhyay, Daniel Campos, Nick Craswell, Jimmy Lin
[36] The Great Nugget Recall: Automating Fact Extraction and RAG Evaluation with Large Language Models
Ronak Pradeep, Nandan Thakur, Shivani Upadhyay, Daniel Campos, Nick Craswell, Jimmy Lin
[35] Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework
Ronak Pradeep, Nandan Thakur, Shivani Upadhyay, Daniel Campos, Nick Craswell, Jimmy Lin
[34] A Large-Scale Study of Relevance Assessments with Large Language Models: An Initial Look
Shivani Upadhyay, Ronak Pradeep, Nandan Thakur, Daniel Campos, Nick Craswell, Ian Soboroff, Hoa Trang Dang, Jimmy Lin
[33] A FIRST Reproduction and Improvements to Single-Token Decoding for Fast Listwise Reranking
Zijian Chen, Ronak Pradeep, Jimmy Lin
[32] Ragnarök: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track
Ronak Pradeep, Nandan Thakur, Sahel Sharifymoghaddam, Eric Zhang, Ryan Nguyen, Daniel Campos, Nick Craswell, Jimmy Lin
[31] Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels
Jasper Xian, Saron Samuel, Faraz Khoubsirat, Ronak Pradeep, Md Arafat Sultan, Radu Florian, Salim Roukos, Avirup Sil, Christopher Potts, Omar Khattab
[30] UMBRELA: UMbrela is the (Open-Source Reproduction of the) Bing RELevance Assessor
Shivani Upadhyay, Ronak Pradeep, Nandan Thakur, Nick Craswell, Jimmy Lin
[29] ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models
Ronak Pradeep, Daniel Lee, Ali Mousavi, Jeffrey Pound, Yisi Sang, Jimmy Lin, Ihab Ilyas, Saloni Potdar, Mostafa Arefiyan, Yunyao Li
[28] Entity Disambiguation via Fusion Entity Decoding
Junxiong Wang, Ali Mousavi, Omar Attia, Ronak Pradeep, Saloni Potdar, Alexander Rush, Umar Farooq Minhas, Yunyao Li
[27] Zero-Shot Cross-Lingual Reranking with Large Language Models for Low-Resource Languages
Mofetoluwa Adeyemi, Akintunde Oladipo, Ronak Pradeep, Jimmy Lin
[26] Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Manveer Singh Tamber, Ronak Pradeep, Jimmy Lin
[25] RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
Ronak Pradeep, Sahel Sharifymoghaddam, Jimmy Lin
[24] RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models
Ronak Pradeep, Sahel Sharifymoghaddam, Jimmy Lin
[23] Vector Search with OpenAI Embeddings: Lucene Is All You Need
Jimmy Lin, Ronak Pradeep, Tommaso Teofili, Jasper Xian
[22] End-to-End Health Misinformation-Free Search with a Large Language Model
Ronak Pradeep, Jimmy Lin
[21] How Does Generative Retrieval Scale to Millions of Passages?
Ronak Pradeep, Kai Hui, Jai Gupta, Adam D Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, Vinh Q Tran
[20] ReadProbe: A Demo of Retrieval-Enhanced Large Language Models to Support Lateral Reading
Dake Zhang, Ronak Pradeep
[19] Zero-Shot Listwise Document Reranking with a Large Language Model
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, Jimmy Lin
[18] Pre-processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering
Manveer Singh Tamber, Ronak Pradeep, Jimmy Lin
[17] PyGaggle: A Gaggle of Resources for Open-Domain Question Answering
Ronak Pradeep, Haonan Chen, Lingwei Gu, Manveer Singh Tamber, Jimmy Lin
[16] Neural Query Synthesis and Domain-Specific Ranking Templates for Multi-Stage Clinical Trial Matching
Ronak Pradeep, Yilin Li, Yuetong Wang, Jimmy Lin
[15] Document Expansion Baselines and Learned Sparse Lexical Representations for MS MARCO v1 and v2
Xueguang Ma, Ronak Pradeep, Rodrigo Nogueira, Jimmy Lin
[14] Another Look at DPR: Reproduction of Training and Replication of Retrieval
Xueguang Ma, Kai Sun, Ronak Pradeep, Minghan Li, Jimmy Lin
[13] New Nails for Old Hammers: Anserini and Pyserini at TREC 2021
Jimmy Lin, Haonen Chen, Chengcheng Hu, Sheng-Chieh Lin, Yilin Li, Xueguang Ma, Ronak Pradeep, Jheng-Hong Yang, Chuan-Ju Wang, Andrew Yates, Xinyu Zhang
[12] Vera: Prediction Techniques for Reducing Harmful Misinformation In Consumer Health Search
Ronak Pradeep, Xueguang Ma, Rodrigo Nogueira, Jimmy Lin
[11] Chatty Goose: A Python Framework for Conversational Search
Edwin Zhang, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, Rodrigo Nogueira, Jimmy Lin
[10] Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, Rodrigo Nogueira
[9] H₂oloo at TAC 2020: Epidemic Question Answering
Justin Borromeo, Ronak Pradeep, Jimmy Lin
[8] Exploring Listwise Evidence Reasoning with T5 for Fact Verification
Kelvin Jiang, Ronak Pradeep, Jimmy Lin
[7] H₂oloo at TREC 2020: When all you got is a Hammer... Deep Learning, Health Misinformation, and Precision Medicine
Ronak Pradeep, Xueguang Ma, Xinyu Zhang, Hang Cui, Ruizhou Xu, Rodrigo Nogueira, Jimmy Lin
[6] Scientific Claim Verification with VerT5erini
Ronak Pradeep, Xueguang Ma, Rodrigo Nogueira, Jimmy Lin
[5] A Replication Study of Dense Passage Retriever
Xueguang Ma, Kai Sun, Ronak Pradeep, Jimmy Lin
[4] Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset
Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Nogueira, Kyunghyun Cho, Hui Fang, Jimmy Lin
[3] The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
Ronak Pradeep, Rodrigo Nogueira, Jimmy Lin
[2] Document Ranking with a Pretrained Sequence-to-Sequence Model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, Jimmy Lin
[1] Foveated Down-Sampling Techniques
Parsa Torabian, Ronak Pradeep, Jeff Orchard, Bryan Tripp
... and a few more papers I might have potentially missed! See my Google Scholar for the complete list.
Playlists
Thanks for making it to here :-) As a token of gratitude and since you asked nicely for it, I shall also introduce you to a few of my Spotify playlists.
ॐ
And everything under the sun is in tune. A music dump of sorts. Updated regularly.
A Day In The Life
An allusion to the Beatles song. Curated by a younger me for a someone who stole my heart. Not updated anymore.
Liebesträume
And what exactly is a dream of love? Here I take on Liszt and attempt to provide a longer answer to aid with my sleep. Updated semi-regularly.