High-Accuracy Low-Precision Training. - Christopher De Sa; Megan Leszczynski; Jian Zhang 049; Alana Marzoev; Christopher R. Aberger; Kunle Olukotun; Christopher Ré (CoRR, 2018)

Low-Memory Neural Network Training: A Technical Report. - Nimit Sharad Sohoni; Christopher Richard Aberger; Megan Leszczynski; Jian Zhang 049; Christopher Ré (CoRR, 2019)

Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. - Tri Dao; Nimit Sharad Sohoni; Albert Gu; Matthew Eichhorn; Amit Blonder; Megan Leszczynski; Atri Rudra; Christopher Ré (ICLR, 2020)

Understanding the Downstream Instability of Word Embeddings. - Megan Leszczynski; Avner May; Jian Zhang 049; Sen Wu 002; Christopher R. Aberger; Christopher Ré (MLSys, 2020)

Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation. - Laurel J. Orr; Megan Leszczynski; Neel Guha; Sen Wu 002; Simran Arora; Xiao Ling; Christopher Ré (CIDR, 2021)

Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text. - Maya Varma; Laurel J. Orr; Sen Wu 002; Megan Leszczynski; Xiao Ling; Christopher Ré (EMNLP (Findings), 2021)

Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems. - Laurel J. Orr; Atindriyo Sanyal; Xiao Ling; Karan Goel; Megan Leszczynski (Proc. VLDB Endow., 2021)

TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval. - Megan Leszczynski; Daniel Y. Fu; Mayee F. Chen; Christopher Ré (ACL (Findings), 2022)

Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset. - Arun Tejasvi Chaganty; Megan Leszczynski; Shu Zhang; Ravi Ganti; Krisztian Balog; Filip Radlinski (SIGIR, 2023)

Generating Synthetic Data for Conversational Music Recommendation Using Random Walks and Language Models. - Megan Leszczynski; Ravi Ganti; Shu Zhang; Krisztian Balog; Filip Radlinski; Fernando Pereira; Arun Tejasvi Chaganty (CoRR, 2023)