Tomasz Korbak

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 38

Top Topics

Sentiment Classification

Kullback Leibler

Top Venues

Trans. Mach. Learn. Res.

Publications

Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey, Rafael Rafailov, Henry Sleight, John Hughes, Tomasz Korbak, Rajashree Agrawal, Dhruv Pai, Andrey Gromov, Daniel A. Roberts, Diyi Yang, David L. Donoho, Sanmi Koyejo
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data. CoRR (2024)
Tomasz Korbak
Aligning language models with human preferences. CoRR (2024)
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman
Compositional Preference Models for Aligning LMs. ICLR (2024)
Angelica Chen, Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez
Learning from Natural Language Feedback. Trans. Mach. Learn. Res. 2024 (2024)
Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR (2024)
Lukas Berglund, Meg Tong, Maximilian Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, Owain Evans
The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A". ICLR (2024)
Mrinank Sharma, Meg Tong, Tomasz Korbak, David Duvenaud, Amanda Askell, Samuel R. Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R. Johnston, Shauna Kravec, Timothy Maxwell, Sam McCandlish, Kamal Ndousse, Oliver Rausch, Nicholas Schiefer, Da Yan, Miranda Zhang, Ethan Perez
Towards Understanding Sycophancy in Language Models. ICLR (2024)
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman
Compositional preference models for aligning LMs. CoRR (2023)
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023)
Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher L. Buckley, Jason Phang, Samuel R. Bowman, Ethan Perez
Pretraining Language Models with Human Preferences. ICML (2023)
Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Bhalerao, Christopher L. Buckley, Jason Phang, Samuel R. Bowman, Ethan Perez
Pretraining Language Models with Human Preferences. CoRR (2023)
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez
Inverse Scaling: When Bigger Isn't Better. CoRR (2023)
Lukas Berglund, Asa Cooper Stickland, Mikita Balesni, Max Kaufmann, Meg Tong, Tomasz Korbak, Daniel Kokotajlo, Owain Evans
Taken out of context: On measuring situational awareness in LLMs. CoRR (2023)
Mrinank Sharma, Meg Tong, Tomasz Korbak, David Duvenaud, Amanda Askell, Samuel R. Bowman, Newton Cheng, Esin Durmus, Zac Hatfield-Dodds, Scott R. Johnston, Shauna Kravec, Timothy Maxwell, Sam McCandlish, Kamal Ndousse, Oliver Rausch, Nicholas Schiefer, Da Yan, Miranda Zhang, Ethan Perez
Towards Understanding Sycophancy in Language Models. CoRR (2023)
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR (2023)
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman
Aligning Language Models with Preferences through f-divergence Minimization. CoRR (2023)
Angelica Chen, Jérémy Scheurer, Tomasz Korbak, Jon Ander Campos, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez
Improving Code Generation by Training with Natural Language Feedback. CoRR (2023)
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez
Inverse Scaling: When Bigger Isn't Better. Trans. Mach. Learn. Res. 2023 (2023)
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman
Aligning Language Models with Preferences through f-divergence Minimization. ICML (2023)
Lukas Berglund, Meg Tong, Max Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, Owain Evans
The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A". CoRR (2023)
Tomasz Korbak
Self-organisation, (M, R)-systems and enactive cognitive science. Adapt. Behav. 31 (1) (2023)
Julian Zubek, Tomasz Korbak, Joanna Raczaszek-Leonardi
Models of symbol emergence in communication: a conceptual review and a guide for avoiding local minima. CoRR (2023)
Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Angelica Chen, Kyunghyun Cho, Ethan Perez
Training Language Models with Language Feedback at Scale. CoRR (2023)
Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting. CoRR (2022)
Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman
Controlling Conditional Language Models without Catastrophic Forgetting. ICML (2022)
Tomasz Korbak, Ethan Perez, Christopher L. Buckley
RL with KL penalties is better viewed as Bayesian inference. EMNLP (Findings) (2022)
Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting. NeurIPS (2022)
Tomasz Korbak, Ethan Perez, Christopher L. Buckley
RL with KL penalties is better viewed as Bayesian inference. CoRR (2022)
Lukasz Kucinski, Tomasz Korbak, Pawel Kolodziej, Piotr Milos
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication. NeurIPS (2021)
Lukasz Kucinski, Tomasz Korbak, Pawel Kolodziej, Piotr Milos
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication. CoRR (2021)
Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman
Controlling Conditional Language Models with Distributional Policy Gradients. CoRR (2021)
Tomasz Korbak, Hady Elsahar, Marc Dymetman, Germán Kruszewski
Energy-Based Models for Code Generation under Compilability Constraints. CoRR (2021)
Krzysztof Glówka, Michal Niklewski, Joanna Wiszowata, Tomasz Korbak, Joanna Raczaszek-Leonardi, Julian Zubek
The Emergence of Action-grounded Compositional Communication. CogSci (2020)
Tomasz Korbak, Julian Zubek, Joanna Raczaszek-Leonardi
Measuring non-trivial compositionality in emergent communication. CoRR (2020)
Renard Korzeniowski, Rafal Rolczynski, Przemyslaw Sadownik, Tomasz Korbak, Marcin Mozejko
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish. CoRR (2019)
Tomasz Korbak, Julian Zubek, Lukasz Kucinski, Piotr Milos, Joanna Raczaszek-Leonardi
Developmentally motivated emergence of compositional communication via template transfer. CoRR (2019)
Tomasz Korbak, Paulina Zak
Fine-Tuning Tree-LSTM for Phrase-Level Sentiment Classification on a Polish Dependency Treebank. LCT (2017)
Tomasz Korbak, Paulina Zak
Fine-tuning Tree-LSTM for phrase-level sentiment classification on a Polish dependency treebank. Submission to PolEval task 2. CoRR (2017)