Alex Tamkin
PhD Student, Computer Science, Stanford University
Email: atamkin_stanford_edu | Twitter: alextamkin
I'm a fifth-year PhD student in Computer Science at Stanford, advised by Noah Goodman and part of the Stanford NLP Group and the Stanford AI Lab.
My research focuses on large pretrained models (e.g. GPT-3) and how we can better build, understand, and control them. I'm especially interested in multimodal and domain-agnostic methods, which have the potential to unlock important applications in healthcare, manufacturing, and the natural sciences.
In the past, I've also worked in reinforcement learning, human-robot interaction, and computational astronomy, and I've spent time at Google Brain, Google Language, and Google Civics.
I'm grateful to be supported by an Open Philanthropy AI Fellowship.
In Fall 2021 I was the instructor of Stanford's CS 197: Computer Science Research. (Slides and materials)
Publications
Active Learning Helps Pretrained Models Learn the Intended Task [🐦thread]
Alex Tamkin*, Dat Nguyen*, Salil Deshpande*, Jesse Mu, Noah GoodmanArXiv PreprintOolong: Investigating What Makes Crosslingual Transfer Hard with Controlled Studies [🐦thread]
Zhengxuan Wu*, Isabel Papadimitriou*, Alex Tamkin*ArXiv PreprintDABS: A Domain-Agnostic Benchmark for Self-Supervised Learning [🌐site] [🐦thread]
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah GoodmanNeurIPS 2021 (Dataset and Benchmarks Track)Press: [Analytics India Magazine] [Stanford HAI]Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study
Ananya Karthik, Mike Wu, Noah Goodman, Alex TamkinNeurIPS 2021 Workshop on Self-Supervised Learning - Theory and PracticeC5T5: Controllable Generation of Organic Molecules with Transformers
Daniel Rothchild, Alex Tamkin, Julie Yu, Ujval Misra, Joseph GonzalezArXiv PreprintOn the Opportunities and Risks of Foundation Models
Center for Research on Foundation Models (full list of authors)Lead: §4.2: Training and Self-Supervision, §4.9: AI Safety and AlignmentCoauthor: §2.2: Vision, §3.3: Education, §4.1 Modeling, §5.6: Ethics of ScaleViewmaker Networks: Learning Views for Unsupervised Representation Learning [📝blogpost] [🐦thread]
Alex Tamkin, Mike Wu, Noah GoodmanICLR 2021Language Through a Prism: A Spectral Approach for Multiscale Language Representations [🐦thread]
Alex Tamkin, Dan Jurafsky, Noah GoodmanNeurIPS 2020Investigating Transferability in Pretrained Language Models [🐦thread]
Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah GoodmanFindings of EMNLP 2020; Presented at CoNLL 2020Distributionally-Aware Exploration for CVaR Bandits.
Alex Tamkin, Ramtin Keramati, Christoph Dann, Emma Brunskill. NeurIPS 2019 Workshop on Safety and Robustness in Decision Making; RLDM 2019Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy
Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill. AAAI 2020Recursive Routing Networks: Learning to Compose Modules for Language Understanding.
Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua D Greene, Dan Jurafsky, Christopher Potts, Lauri KarttunenNAACL 2019Drone.io: A Gestural and Visual Interface for Human-Drone Interaction.
Jessica R Cauchard, Alex Tamkin, Cheng Yao Wang, Luke Vink, Michelle Park, Tommy Fang, James A Landay. HRI 2019 Andrew Vanderburg, Christopher Shallue, Liang Yu, Anne Dattilo, Alex Tamkin. American Astronomical Society Meeting Abstracts, 2019Other Writing
Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models
Alex Tamkin*, Miles Brundage*, Jack Clark, Deep GanguliArXiv. Blogpost: [📝Stanford HAI] Press: [VentureBeat] [Datanami]Input on the European Commission White Paper on Artificial Intelligence
Marietje Schaake, Elisabeth Appel, Dathan M. Duplichen, Lisa Einstein, Wren Elhai, Muhammad Dhafer, Muhammad Faishal, Agata Foryciarz, Sydney L. Frankenberg, Toni Friedman, Zoe Huczok, Kyra Jasper, Danielle Jablanski, Jennifer King, Cindy Kuang, Heajune Lee, Shreya Mantha, Vidyangi Patil, Gailyn Portelance, Adriana Stephan, Alex Tamkin, Alessandro Vecchiato, Eva Zhang, Jason Zhao(See Essays for more)
Personal
Other topics I think a lot about:
Societal impacts of technology, especially machine learning
Mentoring, teaching and fostering a healthy and inclusive research culture
Scientific communication and breaking down walls between fields
Outside of research, I organize the Stanford Queer in AI Dinner with Stanford Inclusion in AI
I also like making art, especially ceramics and photography!