Drone.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)

Recursive 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 Karttunen (NAACL-HLT (1), 2019)

Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. - Ramtin Keramati; Christoph Dann; Alex Tamkin; Emma Brunskill (AAAI, 2020)

Investigating Transferability in Pretrained Language Models. - Alex Tamkin; Trisha Singh; Davide Giovanardi; Noah D. Goodman (EMNLP (Findings), 2020)

Language Through a Prism: A Spectral Approach for Multiscale Language Representations. - Alex Tamkin; Dan Jurafsky; Noah D. Goodman (NeurIPS, 2020)

Viewmaker Networks: Learning Views for Unsupervised Representation Learning. - Alex Tamkin; Mike Wu; Noah D. Goodman (ICLR, 2021)

DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning. - Alex Tamkin; Vincent Liu; Rongfei Lu; Daniel Fein; Colin Schultz; Noah D. Goodman (NeurIPS Datasets and Benchmarks, 2021)

Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models. - Alex Tamkin; Miles Brundage; Jack Clark; Deep Ganguli (CoRR, 2021)

C5T5: Controllable Generation of Organic Molecules with Transformers. - Daniel Rothchild; Alex Tamkin; Julie Yu; Ujval Misra; Joseph Gonzalez 001 (CoRR, 2021)

Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. - Ananya Karthik; Mike Wu; Noah D. Goodman; Alex Tamkin (CoRR, 2021)

DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision. - Alex Tamkin; Gaurab Banerjee; Mohamed Owda; Vincent Liu; Shashank Rammoorthy; Noah D. Goodman (NeurIPS, 2022)

Active Learning Helps Pretrained Models Learn the Intended Task. - Alex Tamkin; Dat Nguyen; Salil Deshpande; Jesse Mu; Noah D. Goodman (NeurIPS, 2022)

Oolong: Investigating What Makes Crosslingual Transfer Hard with Controlled Studies. - Zhengxuan Wu; Isabel Papadimitriou; Alex Tamkin (CoRR, 2022)

Multispectral Contrastive Learning with Viewmaker Networks. - Jasmine Bayrooti; Noah D. Goodman; Alex Tamkin (CVPR Workshops, 2023)

Oolong: Investigating What Makes Transfer Learning Hard with Controlled Studies. - Zhengxuan Wu; Alex Tamkin; Isabel Papadimitriou (EMNLP, 2023)

Task Ambiguity in Humans and Language Models. - Alex Tamkin; Kunal Handa; Avash Shrestha; Noah D. Goodman (ICLR, 2023)

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. - Wai Tong Chung; Bassem Akoush; Pushan Sharma; Alex Tamkin; Ki Sung Jung; Jacqueline Chen; Jack Guo; Davy Brouzet; Mohsen Talei; Bruno Savard; Alexei Y. Poludnenko; Matthias Ihme (NeurIPS, 2023)

Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. - Alex Tamkin; Margalit Glasgow; Xiluo He; Noah D. Goodman (NeurIPS, 2023)

Multispectral Self-Supervised Learning with Viewmaker Networks. - Jasmine Bayrooti; Noah D. Goodman; Alex Tamkin (CoRR, 2023)

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors. - Kathryn Wantlin; Chenwei Wu 006; Shih-Cheng Huang; Oishi Banerjee; Farah Dadabhoy; Veeral Vipin Mehta; Ryan Wonhee Han; Fang Cao; Raja R. Narayan; Errol Colak; Adewole S. Adamson; Laura Heacock; et al. (CoRR, 2023)

Operationalising the Definition of General Purpose AI Systems: Assessing Four Approaches. - Risto Uuk; Carlos Ignacio Gutierrez; Alex Tamkin (CoRR, 2023)

Towards Measuring the Representation of Subjective Global Opinions in Language Models. - Esin Durmus; Karina Nyugen; Thomas I. Liao; Nicholas Schiefer; Amanda Askell; Anton Bakhtin; Carol Chen; Zac Hatfield-Dodds; Danny Hernandez; Nicholas Joseph; Liane Lovitt; Sam McCandlish; et al. (CoRR, 2023)

Studying Large Language Model Generalization with Influence Functions. - Roger B. Grosse; Juhan Bae; Cem Anil; Nelson Elhage; Alex Tamkin; Amirhossein Tajdini; Benoit Steiner; Dustin Li; Esin Durmus; Ethan Perez; Evan Hubinger; Kamile Lukosiute; et al. (CoRR, 2023)

Social Contract AI: Aligning AI Assistants with Implicit Group Norms. - Jan-Philipp Fränken; Sam Kwok; Peixuan Ye; Kanishk Gandhi; Dilip Arumugam; Jared Moore; Alex Tamkin; Tobias Gerstenberg; Noah D. Goodman (CoRR, 2023)

Evaluating and Mitigating Discrimination in Language Model Decisions. - Alex Tamkin; Amanda Askell; Liane Lovitt; Esin Durmus; Nicholas Joseph; Shauna Kravec; Karina Nguyen; Jared Kaplan; Deep Ganguli (CoRR, 2023)

Collective Constitutional AI: Aligning a Language Model with Public Input. - Saffron Huang; Divya Siddarth; Liane Lovitt; Thomas I. Liao; Esin Durmus; Alex Tamkin; Deep Ganguli (FAccT, 2024)

Codebook Features: Sparse and Discrete Interpretability for Neural Networks. - Alex Tamkin; Mohammad Taufeeque; Noah D. Goodman (ICML, 2024)

Many-shot Jailbreaking. - Cem Anil; Esin Durmus; Nina Panickssery; Mrinank Sharma; Joe Benton; Sandipan Kundu; Joshua Batson; Meg Tong; Jesse Mu; Daniel Ford; Francesco Mosconi; Rajashree Agrawal; et al. (NeurIPS, 2024)

Bayesian Preference Elicitation with Language Models. - Kunal Handa; Yarin Gal; Ellie Pavlick; Noah D. Goodman; Jacob Andreas; Alex Tamkin; Belinda Z. Li (CoRR, 2024)

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. - Carson Denison; Monte MacDiarmid; Fazl Barez; David Duvenaud; Shauna Kravec; Samuel Marks; Nicholas Schiefer; Ryan Soklaski; Alex Tamkin; Jared Kaplan; Buck Shlegeris; Samuel R. Bowman; et al. (CoRR, 2024)

Clio: Privacy-Preserving Insights into Real-World AI Use. - Alex Tamkin; Miles McCain; Kunal Handa; Esin Durmus; Liane Lovitt; Ankur Rathi; Saffron Huang; Alfred Mountfield; Jerry Hong; Stuart Ritchie; Michael Stern; Brian Clarke; et al. (CoRR, 2024)

Eliciting Human Preferences with Language Models. - Belinda Z. Li; Alex Tamkin; Noah D. Goodman; Jacob Andreas (ICLR, 2025)

Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. - Kunal Handa; Alex Tamkin; Miles McCain; Saffron Huang; Esin Durmus; Sarah Heck; Jared Mueller; Jerry Hong; Stuart Ritchie; Tim Belonax; Kevin K. Troy; Dario Amodei; et al. (CoRR, 2025)

Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions. - Saffron Huang; Esin Durmus; Miles McCain; Kunal Handa; Alex Tamkin; Jerry Hong; Michael Stern; Arushi Somani; Xiuruo Zhang; Deep Ganguli (CoRR, 2025)