I am a researcher in FAIR at Meta working on improving reasoning capabilities of large language models. Before that, I was a Ph.D. student in the EECS department at the University of California, Berkeley.
I completed my Ph.D. in 2019 on computational tools for immune repertoire characterization and primer set design and was advised by Professor Yun S. Song.
[thesis]
Cornell
I received my Bachelor of Arts and Sciences in both Computer Science and Chemistry in 2014.
Selected Publications
Toolformer: Language Models Can Teach Themselves to Use Tools Timo Schick, Jane Dwivedi-Yu, Roberta Raileanu, Roberto Dessi, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom
Neural Information Processing Systems (NeurIPS), 2023 [Oral Presentation] [paper] [bibtex]
ROBBIE: Robust Bias Evaluation of Large Generative Language Models David Esiobu, Xiaoqing Tan, Saghar Hosseini, Megan Ung, Yuchen Zhang, Jude Fernandes, Jane Dwivedi-Yu, Eleonora Presani, Adina Williams, Eric Michael Smith
Empirical Methods in Natural Language Processing (EMNLP), 2023 [paper]
Active Retrieval Augmented Generation Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig
Empirical Methods in Natural Language Processing (EMNLP), 2023 [paper] [bibtex]
Active Learning Principles for In-Context Learning with Large Language Models Katerina Margatina, Timo Schick, Nikolaos Aletras, Jane Dwivedi-Yu Findings of the Empirical Methods in Natural Language Processing (EMNLP), 2023 [paper] [bibtex]
Augmented Language Models: a Survey Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ram Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom
Transactions on Machine Learning Research (TMLR), 2023 [paper] [bibtex]
Atlas: Few-shot Learning with Retrieval Augmented Language Models Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave
Journal of Machine Learning Research (JMLR), 2023 [paper] [bibtex]
NormBank: A Knowledge Bank of Situational Social Norms Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, Alon Halevy, Diyi Yang
Association of Computational Linguistics (ACL), 2023 [paper] [bibtex]
TimelineQA: A Benchmark for Question Answering over Timelines Wang-Chiew Tan, Jane Dwivedi-Yu, Yuliang Li, Lambert Mathias, Marzieh Saeidi, Nathan Yan, Alon Halevy
Findings of the Association of Computational Linguistics (ACL), 2023 [paper] [bibtex] [code]
Learnings from Data Integration for Augmented Language Models Alon Halevy, Jane Dwivedi-Yu [paper] [bibtex]
Improving Wikipedia Verifiability with AI Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick Lewis, Gautier Izacard, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel
Nature Machine Intelligence, 2023 [paper] [bibtex] [code]
Using Comments for Predicting the Affective Response to Social Media Posts Yi-Chia Wang*, Jane Dwivedi-Yu*, Alon Halevy, Robert E. Kraut
International Conference on Affective Computing and Intelligent Interaction (ACII), 2023
Consequences of Conflicts in Online Conversations Shirley Hayati, Kristen Altenburger, Jane Dwivedi-Yu Robert E. Kraut, Yi-Chia Wang
Under Review
International AAAI Conference on Web and Social Media (ICWSM), 2024
Selective whole-genome amplification reveals population genetics of Leishmania braziliensis directly from patient skin biopsies Olivia A. Pilling, Cooper A. Grace, Joao L. Reis-Cunha, Alexander SF Berry, Matthew W. Mitchell, Jane A. Yu, Clara Malekshahi, Elise Krespan, Christina K. Go, Claudia Lombana, Yun S Song, Camila F Amorim, Alexsandro S. Lago, Lucas P. Carvalho, Edgar M. Carvalho, Dustin Brisson, Phillip Scott, Daniel C. Jeffares, Daniel P. Beiting
PLOS Pathogens, 2023 [paper] [bibtex]
A fast machine-learning-guided primer design pipeline for selective whole genome amplification Jane Dwivedi-Yu, Zachary Oppler, Matthew Mitchell, Yun S. Song, Dustin Brisson
PLOS Computational Biology, 2023 [paper] [bibtex] [code]
EditEval: An Instruction-Based Benchmark for Text Improvements Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni
[paper] [bibtex] [code] [leaderboard]
PEER: A Collaborative Language Model Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel
International Conference on Learning Representations (ICLR), 2023 [paper] [bibtex]
“That’s so cute!”: The CARE Dataset for Affective Response Detection Jane Dwivedi-Yu, Alon Halevy
Computational Natural Language Learning (CoNLL), 2022 [paper] [bibtex] [code]
Affective Signals in a Social Media Recommender System Jane Dwivedi-Yu, Yi-Chia Wang, Lijing Qin, Cristian Canton Ferrer, Alon Halevy
Knowledge Discovery and Data Mining (KDD), 2022 [paper] [bibtex] || [presentation] [poster]
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks Belinda Li, Jane A. Yu, Madian Khabsa, Alon Halevy, Luke Zettlemoyer, Jacob Andreas
North American Chapter of the Association for Computational Linguistics (NAACL), 2022 [paper] [bibtex] [code]
The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems Caleb Ziems, Jane A. Yu, Yi-Chia Wang, Alon Halevy, Diyi Yang
Association of Computational Linguistics (ACL), 2022 [paper] [bibtex] [code]
Understanding Conflicts in Online Conversations Sharon Levy, Robert E. Kraut, Jane A. Yu, Kristen Altenburger, Yi-Chia Wang
International World Wide Web Conference (WWW), 2022 [paper] [bibtex]
Detecting Inspiring Content on Social Media Oana Ignat, Y-Lan Boureau, Jane A. Yu, Alon Halevy
International Conference on Affective Computing and Intelligent Interaction (ACII), 2021 [paper] [bibtex] [code]
Worldwide genetic variation of the IGHV and TRBV immune receptor gene families in humans Shishi Luo*, Jane A. Yu*, Heng Li, and Yun S. Song
Life Science Alliance, 2019 [paper] [bibtex] [code]
Estimating copy number and allelic variation at the immunoglobulin heavy chain locus using short reads Shishi Luo, Jane A. Yu, Heng Li, and Yun S. Song
PLoS Comput Biol, 2016 [paper] [bibtex]