Fazl Barez

According to our database, Fazl Barez authored at least 32 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Best-of-N Jailbreaking.

John Hughes, Sara Price, Aengus Lynch, Rylan Schaeffer, Fazl Barez, Sanmi Koyejo, Henry Sleight, Erik Jones, Ethan Perez, Mrinank Sharma

CoRR, 2024

Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach.

Tony T. Wang, John Hughes, Henry Sleight, Rylan Schaeffer, Rajashree Agrawal, Fazl Barez, Mrinank Sharma, Jesse Mu, Nir Shavit, Ethan Perez

CoRR, 2024

Enhancing Neural Network Interpretability with Feature-Aligned Sparse Autoencoders.

Luke Marks, Alasdair Paren, David Krueger, Fazl Barez

CoRR, 2024

PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning.

Tingchen Fu, Mrinank Sharma, Philip Torr, Shay B. Cohen, David Krueger, Fazl Barez

CoRR, 2024

Towards Interpreting Visual Information Processing in Vision-Language Models.

Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez

CoRR, 2024

Sparse Autoencoders Reveal Universal Feature Spaces Across Large Language Models.

Michael Lan, Philip Torr, Austin Meek, Ashkan Khakzar, David Krueger, Fazl Barez

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, Ethan Perez, Evan Hubinger

CoRR, 2024

Risks and Opportunities of Open-Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Aaron Purewal, Botos Csaba, Fabro Steibel, Fazel Keshtkar, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Thomas Jackson, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 2024

Visualizing Neural Network Imagination.

Nevan Wichers, Victor Tao, Riccardo Volpato, Fazl Barez

CoRR, 2024

Near to Mid-term Risks and Opportunities of Open Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 2024

Increasing Trust in Language Models through the Reuse of Verified Circuits.

Philip Quirke, Clement Neo, Fazl Barez

CoRR, 2024

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam S. Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul F. Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez

CoRR, 2024

Value-Evolutionary-Based Reinforcement Learning.

Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Fazl Barez

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding Addition in Transformers.

Philip Quirke, Fazl Barez

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Interpreting Context Look-ups in Transformers: Investigating Attention-MLP Interactions.

Clement Neo, Shay B. Cohen, Fazl Barez

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models.

Michael Lan, Philip Torr, Fazl Barez

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Large Language Models Relearn Removed Concepts.

Michelle Lo, Fazl Barez, Shay B. Cohen

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Measuring Value Alignment.

Fazl Barez, Philip H. S. Torr

CoRR, 2023

Locating Cross-Task Sequence Continuation Circuits in Transformers.

Michael Lan, Fazl Barez

CoRR, 2023

Interpreting Reward Models in RLHF-Tuned Language Models Using Sparse Autoencoders.

Luke Marks, Amir Abdullah, Luna Mendez, Rauno Arike, Philip H. S. Torr, Fazl Barez

CoRR, 2023

AI Systems of Concern.

Kayla Matteucci, Shahar Avin, Fazl Barez, Seán Ó hÉigeartaigh

CoRR, 2023

DeepDecipher: Accessing and Investigating Neuron Activation in Large Language Models.

Albert Garde, Esben Kran, Fazl Barez

CoRR, 2023

Neuron to Graph: Interpreting Language Model Neurons at Scale.

Alex Foote, Neel Nanda, Esben Kran, Ioannis Konstas, Shay B. Cohen, Fazl Barez

CoRR, 2023

N2G: A Scalable Approach for Quantifying Interpretable Neuron Representations in Large Language Models.

Alex Foote, Neel Nanda, Esben Kran, Ioannis Konstas, Fazl Barez

CoRR, 2023

System III: Learning with Domain Knowledge for Safety Constraints.

Fazl Barez, Hosien Hasanbieg, Alesandro Abbate

CoRR, 2023

Fairness in AI and Its Long-Term Implications on Society.

Ondrej Bohdal, Timothy M. Hospedales, Philip H. S. Torr, Fazl Barez

CoRR, 2023

Exploring the Advantages of Transformers for High-Frequency Trading.

Fazl Barez, Paul Bilokon, Arthur Gervais, Nikita Lisitsyn

CoRR, 2023

Benchmarking Specialized Databases for High-frequency Data.

Fazl Barez, Paul Bilokon, Ruijie Xiong

CoRR, 2023

Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark.

Jason Hoelscher-Obermaier, Julia Persson, Esben Kran, Ioannis Konstas, Fazl Barez

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

The Larger they are, the Harder they Fail: Language Models do not Recognize Identifier Swaps in Python.

Antonio Valerio Miceli Barone, Fazl Barez, Shay B. Cohen, Ioannis Konstas

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2021

ED2: An Environment Dynamics Decomposition Framework for World Model Construction.

Cong Wang, Tianpei Yang, Jianye Hao, Yan Zheng, Hongyao Tang, Fazl Barez, Jinyi Liu, Jiajie Peng, Haiyin Piao, Zhixiao Sun

CoRR, 2021