Hi! I’m Taylor Sorensen, a Computer Science PhD student at the University of Washington advised by Dr. Yejin Choi. My research centers around natural language processing (NLP) and artificial intelligence (AI), with a particular focus on enabling large language models (LLMs) to align better with diverse human perspectives — or, “pluralistic alignment.” I’m broadly interested in the science of LLMs and bridging NLP with human values/subjectivity, reasoning, and applications for social good.

My research has appeared in leading conferences and journals such as ICML, AAAI, ACL, EMNLP, and PNAS, addressing topics ranging from core NLP to pluralistic alignment methodologies to using NLP to enhance democratic discourse and interpersonal understanding.

I’ve been thrilled to see a community grow around pluralistic alignment, including a dedicated NeurIPS workshop and presentations at the Berkeley Simons Institute, Google DeepMind, and the Vienna Alignment Workshop. If you’re interested in pluralistic alignment, I’d love to hear what you’re working on! While I’m quite busy, I try to prioritize being able to give light feedback to people working in the space.

I’ve been lucky enough to intern with amazing teams at Google DeepMind and the Allen Institute for AI. Prior to my PhD, I studied applied mathematics and computer science at Brigham Young University, where I began my research journey under Dr. David Wingate. With Dr. Wingate, I worked on topics including ML-driven soft robotics and foundational projects in prompt engineering and pro-democratic AI. During undergrad, I also had fun experiences like doing ML for a quantitative investment firm, interning doing ML for drug discovery, selling an NLP class project to a startup and teaching competitive programming.

Currently, I’m broadly focused on NLP for domains where there isn’t a single objective ground truth - e.g., subjective judgments, distributional alignment, epistemic uncertainty - and AI for democracy/social good.

Publications

Publications are listed in reverse chronological order. For a list of all publications, see my google scholar profile.

• Value Profiles for Encoding Human Variation
  Taylor Sorensen, Pushkar Mishra, Roma Patel, Michael Henry Tessler, Michiel Bakker, Georgina Evans, Jason Gabriel, Noah Goodman, Verena Rieser
  arXiv Preprint
  Paper

• Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models
  Abhilasha Ravichander, Jillian Fisher, Taylor Sorensen, Ximing Lu, Yuchen Lin, Maria Antoniak, Niloofar Mireshghallah, Chandra Bhagavatula, Yejin Choi
  NAACL 2025
  Paper

• Investigating machine moral judgement through the Delphi experiment
  Liwei Jiang, Jena D Hwang, Chandra Bhagavatula, Ronan Le Bras, Jenny T Liang, Sydney Levine, Jesse Dodge, Keisuke Sakaguchi, Maxwell Forbes, Jack Hessel, Jon Borchardt, Taylor Sorensen, Saadia Gabriel, Yulia Tsvetkov, Oren Etzioni, Maarten Sap, Regina Rini, Yejin Choi
  Nature Machine Intelligence
  Paper

• Can Language Models Reason about Individualistic Human Values and Preferences?
  Liwei Jiang, Taylor Sorensen, Sydney Levin, Yejin Choi
  Arxiv Preprint
  Paper

• Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration
  Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, Yulia Tsvetkov
  EMNLP 2024
  Paper

• A Roadmap to Pluralistic Alignment
  Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi
  ICML 2024 Position Paper
  Paper, Featured in Jack Clark’s Import AI and Interconnects, Invited Talk

• Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale
  Lisa P. Argyle, Christopher A. Bail, Ethan C. Busby, Joshua R. Gubler, Thomas Howe, Christopher Rytting, Taylor Sorensen, David Wingate
  Published in PNAS
  Paper, Science Journal for Kids Adaptation

• Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties
  Taylor Sorensen, Liwei Jiang, Jena Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi
  AAAI 2024 Oral (top 3% of submissions)
  Paper, Presentation, Demo, Code, Dataset, Model, Invited Talk

• NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation
  Peter West, Ronan Bras, Taylor Sorensen, Bill Lin, Liwei Jiang, Ximing Lu, Khyathi Chandu, Jack Hessel, Ashutosh Baheti, Chandra Bhagavatula, Yejin Choi
  Findings of EMNLP 2023
  Paper

• Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing
  Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian Fisher, Taylor Sorensen, Yejin Choi
  NAACL 2024
  Paper

• Towards Coding Social Science Datasets with Language Models
  Christopher Michael Rytting, Taylor Sorensen, Lisa Argyle, Ethan Busby, Nancy Fulda, Joshua Gubler, David Wingate
  Arxiv Preprint
  Paper

• Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models
  David Wingate, Mohammad Shoeybi, Taylor Sorensen
  Findings of EMNLP 2022
  Paper, Code

• An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
  Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate
  ACL 2022
  Paper, Code, Presentation

• Nl-augmenter: A framework for task-sensitive natural language augmentation
  Kaustubh D Dhole, Varun Gangal, Sebastian Gehrmann, …, Taylor Sorensen et al.
  Arxiv Preprint
  Paper, Code

• Using first principles for deep learning and model-based control of soft robots
  Curtis C Johnson, Tyler Quackenbush, Taylor Sorensen, David Wingate, Marc D Killpack
  Frontiers in Robotics and AI
  Paper, Code

Invited Talks

• MilaNLP Pluralistic Alignment: A Roadmap, Recent Work, and Open Problems. Jan 2025
• Berkeley Simons Institute Pluralistic Alignment: A Roadmap, Recent Work, and Open Problems. Oct 2024 Recording
• Dealing with Meaning Variation in NLP, University of Utrecht - AI and Pluralistic Human Values Oct 2024
• University College London Aligning AI with Pluralistic Human Values. Sep 2024
• Vienna Alignment Workshop Pluralistic Alignment. July 2024
• IBM Research AI and Pluralistic Human Values. March 2024
• BuzzRobot AI Community Aligning AI with Pluralistic Human Values. May 2024 Recording

====== Website last updated: Mar 20, 2025