Zac Hatfield-Dodds

Orcid: 0000-0002-8646-8362

According to our database1, Zac Hatfield-Dodds authored at least 22 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Specific versus General Principles for Constitutional AI.
CoRR, 2023

Towards Understanding Sycophancy in Language Models.
CoRR, 2023

Measuring Faithfulness in Chain-of-Thought Reasoning.
CoRR, 2023

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning.
CoRR, 2023

Towards Measuring the Representation of Subjective Global Opinions in Language Models.
CoRR, 2023

The Capacity for Moral Self-Correction in Large Language Models.
CoRR, 2023


2022
Discovering Language Model Behaviors with Model-Written Evaluations.
CoRR, 2022

Constitutional AI: Harmlessness from AI Feedback.
CoRR, 2022

Measuring Progress on Scalable Oversight for Large Language Models.
CoRR, 2022

In-context Learning and Induction Heads.
CoRR, 2022

Toy Models of Superposition.
CoRR, 2022

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.
CoRR, 2022

Language Models (Mostly) Know What They Know.
CoRR, 2022

Scaling Laws and Interpretability of Learning from Repeated Data.
CoRR, 2022

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.
CoRR, 2022

Predictability and Surprise in Large Generative Models.
CoRR, 2022

Deriving Semantics-Aware Fuzzers from Web API Schemas.
Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: Companion Proceedings, 2022


2021
A General Language Assistant as a Laboratory for Alignment.
CoRR, 2021

2020
Falsify your Software: validating scientific code with property-based testing.
Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

2019
Hypothesis: A new approach to property-based testing.
J. Open Source Softw., 2019


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