Taylor Sorensen

Orcid: 0000-0002-3251-3527

According to our database1, Taylor Sorensen authored at least 14 papers between 2021 and 2024.

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

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Can Language Models Reason about Individualistic Human Values and Preferences?
CoRR, 2024

CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting.
CoRR, 2024

A Roadmap to Pluralistic Alignment.
CoRR, 2024

Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Position: A Roadmap to Pluralistic Alignment.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Towards Coding Social Science Datasets with Language Models.
CoRR, 2023

Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing.
CoRR, 2023

NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Using First Principles for Deep Learning and Model-Based Control of Soft Robots.
Frontiers Robotics AI, 2021

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation.
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CoRR, 2021


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