Jared Kaplan

According to our database¹, Jared Kaplan authored at least 32 papers between 2007 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

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

[BibT_eX]

[DOI]

CoRR, 2024

2023

Evaluating and Mitigating Discrimination in Language Model Decisions.

[BibT_eX]

[DOI]

CoRR, 2023

Specific versus General Principles for Constitutional AI.

[BibT_eX]

[DOI]

CoRR, 2023

Studying Large Language Model Generalization with Influence Functions.

[BibT_eX]

[DOI]

CoRR, 2023

Measuring Faithfulness in Chain-of-Thought Reasoning.

[BibT_eX]

[DOI]

CoRR, 2023

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Discovering Language Model Behaviors with Model-Written Evaluations.

[BibT_eX]

[DOI]

Timothy Telleen-Lawton

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

2022

Scaling Laws from the Data Manifold Dimension.

[BibT_eX]

[DOI]

Utkarsh Sharma

Jared Kaplan

J. Mach. Learn. Res., 2022

Discovering Language Model Behaviors with Model-Written Evaluations.

[BibT_eX]

[DOI]

Timothy Telleen-Lawton

CoRR, 2022

Constitutional AI: Harmlessness from AI Feedback.

[BibT_eX]

[DOI]

CoRR, 2022

Measuring Progress on Scalable Oversight for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2022

In-context Learning and Induction Heads.

[BibT_eX]

[DOI]

CoRR, 2022

Toy Models of Superposition.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Language Models (Mostly) Know What They Know.

[BibT_eX]

[DOI]

CoRR, 2022

Scaling Laws and Interpretability of Learning from Repeated Data.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Predictability and Surprise in Large Generative Models.

[BibT_eX]

[DOI]

CoRR, 2022

Predictability and Surprise in Large Generative Models.

[BibT_eX]

[DOI]

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

A General Language Assistant as a Laboratory for Alignment.

[BibT_eX]

[DOI]

CoRR, 2021

Evaluating Large Language Models Trained on Code.

[BibT_eX]

[DOI]

Henrique Pondé de Oliveira Pinto

CoRR, 2021

Explaining Neural Scaling Laws.

[BibT_eX]

[DOI]

CoRR, 2021

Scaling Laws for Transfer.

[BibT_eX]

[DOI]

CoRR, 2021

Data and Parameter Scaling Laws for Neural Machine Translation.

[BibT_eX]

[DOI]

Mitchell A. Gordon

Kevin Duh

Jared Kaplan

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Scaling Laws for Autoregressive Generative Modeling.

[BibT_eX]

[DOI]

CoRR, 2020

A Neural Scaling Law from the Dimension of the Data Manifold.

[BibT_eX]

[DOI]

Utkarsh Sharma

Jared Kaplan

CoRR, 2020

Scaling Laws for Neural Language Models.

[BibT_eX]

[DOI]

CoRR, 2020

Language Models are Few-Shot Learners.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

An Empirical Model of Large-Batch Training.

[BibT_eX]

[DOI]

CoRR, 2018

2007

Explaining Debugging Strategies to End-User Programmers.

[BibT_eX]

[DOI]

Neeraja Subrahmaniyan

Proceedings of the 2007 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2007), 2007

Jared Kaplan

Timeline

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On csauthors.net:

Bibliography

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