Alec Radford - RankMe

33 papers A* 9Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning a Generative Meta-Model of LLM Activations. CoRR Grace Luo, Jiahai Feng, Trevor Darrell, Alec Radford, Jacob Steinhardt
2026	J	`jnl`	Shaping capabilities with token-level data filtering. CoRR Neil Rathi, Alec Radford
2025	A*	`conf`	Scaling and evaluating sparse autoencoders. ICLR Leo Gao, Tom Dupré la Tour, Henk Tillman, Gabriel Goh, Rajan Troll, Alec Radford, Ilya Sutskever, Jan Leike, Jeffrey Wu
2024	J	`jnl`	Scaling and evaluating sparse autoencoders. CoRR Leo Gao, Tom Dupré la Tour, Henk Tillman, Gabriel Goh, Rajan Troll, Alec Radford, Ilya Sutskever, Jan Leike, Jeffrey Wu
2023	A*	`conf`	Robust Speech Recognition via Large-Scale Weak Supervision. ICML Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, Ilya Sutskever
2022	J	`jnl`	Robust Speech Recognition via Large-Scale Weak Supervision. CoRR Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, Ilya Sutskever
2022	J	`jnl`	Text and Code Embeddings by Contrastive Pre-Training. CoRR Arvind Neelakantan, Tao Xu, Raul Puri, Alec Radford, Jesse Michael Han, Jerry Tworek, Qiming Yuan, Nikolas Tezak, Jong Wook Kim, Chris Hallacy, Johannes Heidecke, Pranav Shyam, Boris Power, Tyna Eloundou Nekoul, Girish Sastry, Gretchen Krueger, David Schnurr, Felipe Petroski Such, Kenny Hsu, Madeleine Thompson, Tabarak Khan, Toki Sherbakov, Joanne Jang, Peter Welinder, Lilian Weng
2021	J	`jnl`	Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications. CoRR Sandhini Agarwal, Gretchen Krueger, Jack Clark, Alec Radford, Jong Wook Kim, Miles Brundage
2021	J	`jnl`	Evaluating Large Language Models Trained on Code. CoRR Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba
2021	A*	`conf`	Learning Transferable Visual Models From Natural Language Supervision. ICML Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever
2021	J	`jnl`	Learning Transferable Visual Models From Natural Language Supervision. CoRR Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever
2021	J	`jnl`	Unsupervised Neural Machine Translation with Generative Language Models Only. CoRR Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever
2021	A*	`conf`	Zero-Shot Text-to-Image Generation. ICML Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
2021	J	`jnl`	Zero-Shot Text-to-Image Generation. CoRR Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
2020	A*	`conf`	Distribution Augmentation for Generative Modeling. ICML Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever
2020	A*	`conf`	Generative Pretraining From Pixels. ICML Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever
2020	J	`jnl`	Jukebox: A Generative Model for Music. CoRR Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever
2020	A*	`conf`	Language Models are Few-Shot Learners. NeurIPS Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei
2020	J	`jnl`	Language Models are Few-Shot Learners. CoRR Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei
2020	J	`jnl`	Learning to summarize from human feedback. CoRR Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, Paul F. Christiano
2020	A*	`conf`	Learning to summarize with human feedback. NeurIPS Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, Paul F. Christiano
2020	J	`jnl`	Scaling Laws for Autoregressive Generative Modeling. CoRR Tom Henighan, Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun, Tom B. Brown, Prafulla Dhariwal, Scott Gray, Chris Hallacy, Benjamin Mann, Alec Radford, Aditya Ramesh, Nick Ryder, Daniel M. Ziegler, John Schulman, Dario Amodei, Sam McCandlish
2020	J	`jnl`	Scaling Laws for Neural Language Models. CoRR Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, Dario Amodei
2019	J	`jnl`	Fine-Tuning Language Models from Human Preferences. CoRR Daniel M. Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B. Brown, Alec Radford, Dario Amodei, Paul F. Christiano, Geoffrey Irving
2019	J	`jnl`	Generating Long Sequences with Sparse Transformers. CoRR Rewon Child, Scott Gray, Alec Radford, Ilya Sutskever
2019	J	`jnl`	Release Strategies and the Social Impacts of Language Models. CoRR Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Jasmine Wang
2018	—	`conf`	Improving GANs Using Optimal Transport. ICLR (Poster) Tim Salimans, Han Zhang, Alec Radford, Dimitris N. Metaxas
2018	J	`jnl`	Improving GANs Using Optimal Transport. CoRR Tim Salimans, Han Zhang, Alec Radford, Dimitris N. Metaxas
2017	J	`jnl`	Learning to Generate Reviews and Discovering Sentiment. CoRR Alec Radford, Rafal Józefowicz, Ilya Sutskever
2017	J	`jnl`	Proximal Policy Optimization Algorithms. CoRR John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov
2016	—	`conf`	Improved Techniques for Training GANs. NIPS Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	J	`jnl`	Improved Techniques for Training GANs. CoRR Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	A*	`conf`	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. ICLR (Poster) Alec Radford, Luke Metz, Soumith Chintala