Mayee F. Chen

According to our database, Mayee F. Chen authored at least 23 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Aioli: A Unified Optimization Framework for Language Model Data Mixing.

Mayee F. Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Ré

CoRR, 2024

Cookbook: A framework for improving LLM generative abilities via programmatic data generating templates.

Avanika Narayan, Mayee F. Chen, Kush Bhatia, Christopher Ré

CoRR, 2024

Archon: An Architecture Search Framework for Inference-Time Techniques.

Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Guha, Estefany Kelly Buchanan, Mayee F. Chen, Neel Guha, Christopher Ré, Azalia Mirhoseini

CoRR, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

CoRR, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Smoothie: Label Free Language Model Routing.

Neel Guha, Mayee F. Chen, Trevor Chow, Ishan S. Khare, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

A case for reframing automated medical image classification as segmentation.

Sarah M. Hooper, Mayee F. Chen, Khaled Saab, Kush Bhatia, Curtis P. Langlotz, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification.

Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Skill-it! A data-driven skills framework for understanding and training language models.

Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Ask Me Anything: A simple strategy for prompting language models.

Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Christopher Ré

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

An Adversarial Model of Network Disruption: Maximizing Disagreement and Polarization in Social Networks.

Mayee F. Chen, Miklós Z. Rácz

IEEE Trans. Netw. Sci. Eng., 2022

Resonant Anomaly Detection with Multiple Reference Datasets.

Mayee F. Chen, Benjamin Nachman, Frederic Sala

CoRR, 2022

Ask Me Anything: A simple strategy for prompting language models.

Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré

CoRR, 2022

Shoring up the foundations: fusing model embeddings and weak supervision.

Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity.

Khaled Saab, Sarah M. Hooper, Mayee F. Chen, Michael Zhang, Daniel L. Rubin, Christopher Ré

Proceedings of the Machine Learning for Healthcare Conference, 2022

Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning.

Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2022

TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval.

Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen, Christopher Ré

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Mandoline: Model Evaluation under Distribution Shift.

Mayee F. Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Ré

Proceedings of the 38th International Conference on Machine Learning, 2021

Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation.

Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Ré

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings.

Mayee F. Chen, Daniel Y. Fu, Frederic Sala, Sen Wu, Ravi Teja Mullapudi, Fait Poms, Kayvon Fatahalian, Christopher Ré

CoRR, 2020

Network disruption: maximizing disagreement and polarization in social networks.

Mayee F. Chen, Miklós Z. Rácz

CoRR, 2020

Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods.

Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré

Proceedings of the 37th International Conference on Machine Learning, 2020

2014

Efficient GCD Computation for Big Integers on Xeon Phi Coprocessor.

Jie Chen, William Watson, Mayee F. Chen

Proceedings of the 9th IEEE International Conference on Networking, 2014