D
David Luan
Researcher at OpenAI
Publications - 2
Citations - 2278
David Luan is an academic researcher from OpenAI. The author has contributed to research in topics: Computer science. The author has an hindex of 1, co-authored 1 publications receiving 283 citations.
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Journal Article
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery,Sharan Narang,Jacob Devlin,Maarten Bosma,Gaurav Mishra,Adam Roberts,Paul Barham,Hyung Won Chung,Charles Sutton,Sebastian Gehrmann,Parker Schuh,Kensen Shi,Sasha Tsvyashchenko,Joshua Maynez,Abhishek Rao,Parker Barnes,Yi Tay,Noam Shazeer,Velu Prabhakaran,Emily Reif,Nan Du,B. C. Hutchinson,Reiner Pope,James Bradbury,Jacob Austin,Michael Isard,Guy Gur-Ari,Peng Yin,Toju Duke,Anselm Levskaya,Sanjay Ghemawat,Sunipa Dev,Henryk Michalewski,Xavier Garcia,Vedant Misra,Kevin Robinson,L Fedus,Denny Zhou,Daphne Ippolito,David Luan,Hyeontaek Lim,Barret Zoph,Alexander Spiridonov,Ryan Sepassi,David Dohan,Shivani Agrawal,Mark Omernick,Andrew M. Dai,Thanumalayan Sankaranarayana Pillai,Marie Pellat,Aitor Lewkowycz,Erica Oliveira Moreira,Rewon Child,Oleksandr Polozov,Katherine Lee,Zong Tuan Zhou,Xuezhi Wang,Brennan Saeta,Mark Díaz,Orhan Firat,M. Catasta,Jason Loh Seong Wei,Kathleen S. Meier-Hellstern,Douglas Eck,Jeffrey Dean,Slav Petrov,Noah Fiedel +66 more
TL;DR: A 540-billion parameter, densely activated, Transformer language model, which is called PaLM achieves breakthrough performance, outperforming the state-of-the-art on a suite of multi-step reasoning tasks, and outperforming average human performance on the recently released BIG-bench benchmark.
Proceedings Article
Generative Pretraining From Pixels
TL;DR: This work trains a sequence Transformer to auto-regressively predict pixels, without incorporating knowledge of the 2D input structure, and finds that a GPT-2 scale model learns strong image representations as measured by linear probing, fine-tuning, and low-data classification.