Alex Tamkin - RankMe

48 papers A* 13Journal 30Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	How AI Impacts Skill Formation. CoRR Judy Hanwen Shen, Alex Tamkin
2025	J	`jnl`	Anthropic Economic Index report: Uneven geographic and enterprise AI adoption. CoRR Ruth E. Appel, Peter McCrory, Alex Tamkin, Miles McCain, Tyler Neylon, Michael Stern
2025	A*	`conf`	Eliciting Human Preferences with Language Models. ICLR Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas
2025	J	`jnl`	Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions. CoRR Saffron Huang, Esin Durmus, Miles McCain, Kunal Handa, Alex Tamkin, Jerry Hong, Michael Stern, Arushi Somani, Xiuruo Zhang, Deep Ganguli
2025	J	`jnl`	Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. CoRR Kunal Handa, Alex Tamkin, Miles McCain, Saffron Huang, Esin Durmus, Sarah Heck, Jared Mueller, Jerry Hong, Stuart J. Ritchie, Tim Belonax, Kevin K. Troy, Dario Amodei, Jared Kaplan, Jack Clark, Deep Ganguli
2024	J	`jnl`	Bayesian Preference Elicitation with Language Models. CoRR Kunal Handa, Yarin Gal, Ellie Pavlick, Noah D. Goodman, Jacob Andreas, Alex Tamkin, Belinda Z. Li
2024	J	`jnl`	Clio: Privacy-Preserving Insights into Real-World AI Use. CoRR Alex Tamkin, Miles McCain, Kunal Handa, Esin Durmus, Liane Lovitt, Ankur Rathi, Saffron Huang, Alfred Mountfield, Jerry Hong, Stuart J. Ritchie, Michael Stern, Brian Clarke, Landon Goldberg, Theodore R. Sumers, Jared Mueller, William McEachen, Wes Mitchell, Shan Carter, Jack Clark, Jared Kaplan, Deep Ganguli
2024	A*	`conf`	Codebook Features: Sparse and Discrete Interpretability for Neural Networks. ICML Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman
2024	—	`conf`	Collective Constitutional AI: Aligning a Language Model with Public Input. FAccT Saffron Huang, Divya Siddarth, Liane Lovitt, Thomas I. Liao, Esin Durmus, Alex Tamkin, Deep Ganguli
2024	J	`jnl`	Collective Constitutional AI: Aligning a Language Model with Public Input. CoRR Saffron Huang, Divya Siddarth, Liane Lovitt, Thomas I. Liao, Esin Durmus, Alex Tamkin, Deep Ganguli
2024	A*	`conf`	Many-shot Jailbreaking. NeurIPS Cem Anil, Esin Durmus, Nina Panickssery, Mrinank Sharma, Joe Benton, Sandipan Kundu, Joshua Batson, Meg Tong, Jesse Mu, Daniel Ford, Francesco Mosconi, Rajashree Agrawal, Rylan Schaeffer, Naomi Bashkansky, Samuel Svenningsen, Mike Lambert, Ansh Radhakrishnan, Carson Denison, Evan Hubinger, Yuntao Bai, Trenton Bricken, Timothy Maxwell, Nicholas Schiefer, James Sully, Alex Tamkin, Tamera Lanham, Karina Nguyen, Tomek Korbak, Jared Kaplan, Deep Ganguli, Samuel R. Bowman, Ethan Perez, Roger B. Grosse, David Kristjanson Duvenaud
2024	J	`jnl`	Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models. CoRR 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, Ethan Perez, Evan Hubinger
2023	J	`jnl`	BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors. CoRR Kathryn Wantlin, Chenwei Wu, 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, Geoffrey H. Tison, Alex Tamkin, Pranav Rajpurkar
2023	J	`jnl`	Codebook Features: Sparse and Discrete Interpretability for Neural Networks. CoRR Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman
2023	J	`jnl`	Eliciting Human Preferences with Language Models. CoRR Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas
2023	J	`jnl`	Evaluating and Mitigating Discrimination in Language Model Decisions. CoRR Alex Tamkin, Amanda Askell, Liane Lovitt, Esin Durmus, Nicholas Joseph, Shauna Kravec, Karina Nguyen, Jared Kaplan, Deep Ganguli
2023	A*	`conf`	Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. NeurIPS Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
2023	—	`conf`	Multispectral Contrastive Learning with Viewmaker Networks. CVPR Workshops Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
2023	J	`jnl`	Multispectral Self-Supervised Learning with Viewmaker Networks. CoRR Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
2023	A*	`conf`	Oolong: Investigating What Makes Transfer Learning Hard with Controlled Studies. EMNLP Zhengxuan Wu, Alex Tamkin, Isabel Papadimitriou
2023	J	`jnl`	Operationalising the Definition of General Purpose AI Systems: Assessing Four Approaches. CoRR Risto Uuk, Carlos Ignacio Gutierrez, Alex Tamkin
2023	J	`jnl`	Social Contract AI: Aligning AI Assistants with Implicit Group Norms. CoRR Jan-Philipp Fränken, Sam Kwok, Peixuan Ye, Kanishk Gandhi, Dilip Arumugam, Jared Moore, Alex Tamkin, Tobias Gerstenberg, Noah D. Goodman
2023	J	`jnl`	Studying Large Language Model Generalization with Influence Functions. CoRR 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, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, Samuel R. Bowman
2023	A*	`conf`	Task Ambiguity in Humans and Language Models. ICLR Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman
2023	J	`jnl`	Towards Measuring the Representation of Subjective Global Opinions in Language Models. CoRR 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, Orowa Sikder, Alex Tamkin, Janel Thamkul, Jared Kaplan, Jack Clark, Deep Ganguli
2023	A*	`conf`	Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. NeurIPS 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
2023	J	`jnl`	Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. CoRR Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung, Jacqueline H. Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bruno Savard, Alexei Y. Poludnenko, Matthias Ihme
2022	A*	`conf`	Active Learning Helps Pretrained Models Learn the Intended Task. NeurIPS Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
2022	J	`jnl`	Active Learning Helps Pretrained Models Learn the Intended Task. CoRR Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
2022	A*	`conf`	DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision. NeurIPS Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah D. Goodman
2022	J	`jnl`	Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. CoRR Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
2022	J	`jnl`	Oolong: Investigating What Makes Crosslingual Transfer Hard with Controlled Studies. CoRR Zhengxuan Wu, Isabel Papadimitriou, Alex Tamkin
2022	J	`jnl`	Task Ambiguity in Humans and Language Models. CoRR Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman
2021	J	`jnl`	C5T5: Controllable Generation of Organic Molecules with Transformers. CoRR Daniel Rothchild, Alex Tamkin, Julie Yu, Ujval Misra, Joseph Gonzalez
2021	J	`jnl`	DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning. CoRR Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
2021	—	`conf`	DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning. NeurIPS Datasets and Benchmarks Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
2021	J	`jnl`	Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin
2021	J	`jnl`	Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models. CoRR Alex Tamkin, Miles Brundage, Jack Clark, Deep Ganguli
2021	A*	`conf`	Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR Alex Tamkin, Mike Wu, Noah D. Goodman
2020	A*	`conf`	Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. AAAI Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
2020	—	`conf`	Investigating Transferability in Pretrained Language Models. EMNLP (Findings) Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman
2020	J	`jnl`	Investigating Transferability in Pretrained Language Models. CoRR Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman
2020	A*	`conf`	Language Through a Prism: A Spectral Approach for Multiscale Language Representations. NeurIPS Alex Tamkin, Dan Jurafsky, Noah D. Goodman
2020	J	`jnl`	Language Through a Prism: A Spectral Approach for Multiscale Language Representations. CoRR Alex Tamkin, Dan Jurafsky, Noah D. Goodman
2020	J	`jnl`	Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR Alex Tamkin, Mike Wu, Noah D. Goodman
2019	J	`jnl`	Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. CoRR Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
2019	A*	`conf`	Drone.io: A Gestural and Visual Interface for Human-Drone Interaction. HRI Jessica R. Cauchard, Alex Tamkin, Cheng Yao Wang, Luke Vink, Michelle Park, Tommy Fang, James A. Landay
2019	—	`conf`	Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL-HLT (1) 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