Entropy Generation of Desalination Powered by Variable Temperature Waste Heat. - David M. Warsinger; Karan H. Mistry; Kishor G. Nayar; Hyung Won Chung; John H. Lienhard V (Entropy, 2015)

Improving Multilingual Models with Language-Clustered Vocabularies. - Hyung Won Chung; Dan Garrette; Kiat Chuan Tan; Jason Riesa (EMNLP (1), 2020)

Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task. - Thibault Sellam; Amy Pu; Hyung Won Chung; Sebastian Gehrmann; Qijun Tan; Markus Freitag; Dipanjan Das 001; Ankur P. Parikh (WMT@EMNLP, 2020)

Finding Fast Transformers: One-Shot Neural Architecture Search by Component Composition. - Henry Tsai; Jayden Ooi; Chun-Sung Ferng; Hyung Won Chung; Jason Riesa (CoRR, 2020)

A Simple and Effective Positional Encoding for Transformers. - Pu-Chin Chen; Henry Tsai; Srinadh Bhojanapalli; Hyung Won Chung; Yin-Wen Chang; Chun-Sung Ferng (EMNLP (1), 2021)

Do Transformer Modifications Transfer Across Implementations and Applications? - Sharan Narang; Hyung Won Chung; Yi Tay; Liam Fedus; Thibault Févry; Michael Matena; Karishma Malkan; Noah Fiedel; Noam Shazeer; Zhenzhong Lan; Yanqi Zhou; Wei Li 133; et al. (EMNLP (1), 2021)

Learning Compact Metrics for MT. - Amy Pu; Hyung Won Chung; Ankur P. Parikh; Sebastian Gehrmann; Thibault Sellam (EMNLP (1), 2021)

Rethinking Embedding Coupling in Pre-trained Language Models. - Hyung Won Chung; Thibault Févry; Henry Tsai; Melvin Johnson; Sebastian Ruder (ICLR, 2021)

Neural Data Augmentation via Example Extrapolation. - Kenton Lee; Kelvin Guu; Luheng He; Tim Dozat; Hyung Won Chung (CoRR, 2021)

Demystifying the Better Performance of Position Encoding Variants for Transformer. - Pu-Chin Chen; Henry Tsai; Srinadh Bhojanapalli; Hyung Won Chung; Yin-Wen Chang; Chun-Sung Ferng (CoRR, 2021)

Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers. - Yi Tay; Mostafa Dehghani 001; Jinfeng Rao; William Fedus; Samira Abnar; Hyung Won Chung; Sharan Narang; Dani Yogatama; Ashish Vaswani; Donald Metzler (CoRR, 2021)

Scale Efficiently: Insights from Pretraining and Finetuning Transformers. - Yi Tay; Mostafa Dehghani 001; Jinfeng Rao; William Fedus; Samira Abnar; Hyung Won Chung; Sharan Narang; Dani Yogatama; Ashish Vaswani; Donald Metzler (ICLR, 2022)

Charformer: Fast Character Transformers via Gradient-based Subword Tokenization. - Yi Tay; Vinh Q. Tran 002; Sebastian Ruder; Jai Prakash Gupta 001; Hyung Won Chung; Dara Bahri; Zhen Qin 001; Simon Baumgartner; Cong Yu 001; Donald Metzler (ICLR, 2022)

What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization? - Thomas Wang; Adam Roberts; Daniel Hesslow; Teven Le Scao; Hyung Won Chung; Iz Beltagy; Julien Launay; Colin Raffel (ICML, 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; et al. (CoRR, 2022)

What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? - Thomas Wang; Adam Roberts; Daniel Hesslow; Teven Le Scao; Hyung Won Chung; Iz Beltagy; Julien Launay; Colin Raffel (CoRR, 2022)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Eric Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (CoRR, 2022)

Large Language Models Encode Clinical Knowledge. - Karan Singhal; Shekoofeh Azizi; Tao Tu 001; S. Sara Mahdavi; Jason Wei; Hyung Won Chung; Nathan Scales; Ajay Kumar Tanwani; Heather Cole-Lewis; Stephen Pfohl; Perry Payne; Martin Seneviratne; et al. (CoRR, 2022)

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. - Mirac Suzgun; Nathan Scales; Nathanael Schärli; Sebastian Gehrmann; Yi Tay; Hyung Won Chung; Aakanksha Chowdhery; Quoc V. Le; Ed H. Chi; Denny Zhou; Jason Wei (ACL (Findings), 2023)

Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? - Yi Tay; Mostafa Dehghani 001; Samira Abnar; Hyung Won Chung; William Fedus; Jinfeng Rao; Sharan Narang; Vinh Q. Tran 002; Dani Yogatama; Donald Metzler (EMNLP (Findings), 2023)

Transcending Scaling Laws with 0.1% Extra Compute. - Yi Tay; Jason Wei; Hyung Won Chung; Vinh Q. Tran 002; David R. So; Siamak Shakeri; Xavier Garcia; Huaixiu Steven Zheng; Jinfeng Rao; Aakanksha Chowdhery; Denny Zhou; Donald Metzler; et al. (EMNLP, 2023)

UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining. - Hyung Won Chung; Xavier Garcia; Adam Roberts; Yi Tay; Orhan Firat; Sharan Narang; Noah Constant (ICLR, 2023)

Language models are multilingual chain-of-thought reasoners. - Freda Shi; Mirac Suzgun; Markus Freitag; Xuezhi Wang 002; Suraj Srivats; Soroush Vosoughi; Hyung Won Chung; Yi Tay; Sebastian Ruder; Denny Zhou; Dipanjan Das 001; Jason Wei (ICLR, 2023)

UL2: Unifying Language Learning Paradigms. - Yi Tay; Mostafa Dehghani 001; Vinh Q. Tran 002; Xavier Garcia; Jason Wei; Xuezhi Wang 002; Hyung Won Chung; Dara Bahri; Tal Schuster; Huaixiu Steven Zheng; Denny Zhou; Neil Houlsby; et al. (ICLR, 2023)

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. - Shayne Longpre; Le Hou; Tu Vu; Albert Webson; Hyung Won Chung; Yi Tay; Denny Zhou; Quoc V. Le; Barret Zoph; Jason Wei; Adam Roberts (ICML, 2023)

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. - Sheng Shen 001; Le Hou; Yanqi Zhou; Nan Du 002; Shayne Longpre; Jason Wei; Hyung Won Chung; Barret Zoph; William Fedus; Xinyun Chen; Tu Vu; Yuexin Wu; et al. (CoRR, 2023)

PaLM: Scaling Language Modeling with Pathways. - Aakanksha Chowdhery; Sharan Narang; Jacob Devlin; Maarten Bosma; Gaurav Mishra; Adam Roberts; Paul Barham 001; Hyung Won Chung; Charles Sutton; Sebastian Gehrmann; Parker Schuh; Kensen Shi; et al. (J. Mach. Learn. Res., 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; et al. (J. Mach. Learn. Res., 2023)

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models. - Sheng Shen 001; Le Hou; Yanqi Zhou; Nan Du 002; Shayne Longpre; Jason Wei; Hyung Won Chung; Barret Zoph; William Fedus; Xinyun Chen; Tu Vu; Yuexin Wu; et al. (ICLR, 2024)

Measuring short-form factuality in large language models. - Jason Wei; Nguyen Karina; Hyung Won Chung; Yunxin Joy Jiao; Spencer Papay; Amelia Glaese; John Schulman; William Fedus (CoRR, 2024)

Deliberative Alignment: Reasoning Enables Safer Language Models. - Melody Y. Guan; Manas Joglekar; Eric Wallace; Saachi Jain; Boaz Barak; Alec Helyar; Rachel Dias; Andrea Vallone; Hongyu Ren; Jason Wei; Hyung Won Chung; Sam Toyer; et al. (CoRR, 2024)

OpenAI o1 System Card. - Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney; Alex Iftimie; Alex Karpenko; et al. (CoRR, 2024)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Yunxuan Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (J. Mach. Learn. Res., 2024)

BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents. - Jason Wei; Zhiqing Sun; Spencer Papay; Scott McKinney; Jeffrey Han; Isa Fulford; Hyung Won Chung; Alex Tachard Passos; William Fedus; Amelia Glaese (CoRR, 2025)