Brian Lester

According to our database, Brian Lester authored at least 18 papers between 2019 and 2024.

Collaborative distances:

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

2024

Advancements in Constitutive Model Calibration: Leveraging the Power of Full-Field DIC Measurements and In-Situ Load Path Selection for Reliable Parameter Inference.

Denielle Ricciardi, Tom Seidl, Brian Lester, Amanda Jones, Elizabeth Jones

CoRR, 2024

Realistic Evaluation of Model Merging for Compositional Generalization.

Derek Tam, Yash Kant, Brian Lester, Igor Gilitschenski, Colin Raffel

CoRR, 2024

Training LLMs over Neurally Compressed Text.

Brian Lester, Jaehoon Lee, Alex Alemi, Jeffrey Pennington, Adam Roberts, Jascha Sohl-Dickstein, Noah Constant

CoRR, 2024

2023

Scaling Up Models and Data with t5x and seqio.

Adam Roberts, Hyung Won Chung, Gaurav Mishra, Anselm Levskaya, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Kehang Han, Michelle Casbon, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo

J. Mach. Learn. Res., 2023

Bayesian Optimal Experimental Design for Constitutive Model Calibration.

Denielle Ricciardi, Tom Seidl, Brian Lester, Amanda Jones, Elizabeth Jones

CoRR, 2023

Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models.

Nikhil Kandpal, Brian Lester, Mohammed Muqeeth, Anisha Mascarenhas, Monty Evans, Vishal Baskaran, Tenghao Huang, Haokun Liu, Colin Raffel

Proceedings of the International Conference on Machine Learning, 2023

2022

Reducing Retraining by Recycling Parameter-Efficient Prompts.

Brian Lester, Joshua Yurtsever, Siamak Shakeri, Noah Constant

CoRR, 2022

Scaling Up Models and Data with t5x and seqio.

Adam Roberts, Hyung Won Chung, Anselm Levskaya, Gaurav Mishra, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo

CoRR, 2022

Finetuned Language Models are Zero-Shot Learners.

Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le

Proceedings of the Tenth International Conference on Learning Representations, 2022

Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation.

Tu Vu, Aditya Barua, Brian Lester, Daniel Cer, Mohit Iyyer, Noah Constant

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer.

Tu Vu, Brian Lester, Noah Constant, Rami Al-Rfou', Daniel Cer

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Intent Features for Rich Natural Language Understanding.

Brian Lester, Sagnik Ray Choudhury, Rashmi Prasad, Srinivas Bangalore

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers, 2021

The Power of Scale for Parameter-Efficient Prompt Tuning.

Brian Lester, Rami Al-Rfou, Noah Constant

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

iobes: A Library for Span-Level Processing.

Brian Lester

CoRR, 2020

Multiple Word Embeddings for Increased Diversity of Representation.

Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury, Srinivas Bangalore

CoRR, 2020

Leader: Prefixing a Length for Faster Word Vector Serialization.

Brian Lester

CoRR, 2020

Constrained Decoding for Computationally Efficient Named Entity Recognition Taggers.

Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury, Srinivas Bangalore

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

An Effective Label Noise Model for DNN Text Classification.

Ishan Jindal, Daniel Pressel, Brian Lester, Matthew S. Nokleby

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019