Fazl Barez

According to our database, Fazl Barez authored at least 19 papers between 2021 and 2024.

Collaborative distances:

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

2024

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

Clement Neo, Shay B. Cohen, Fazl Barez

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

Large Language Models Relearn Removed Concepts.

Michelle Lo, Shay B. Cohen, Fazl Barez

CoRR, 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

Understanding Addition in Transformers.

Philip Quirke, 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