Statistical and Computational Guarantees for Influence Diagnostics. - Jillian Fisher; Lang Liu; Krishna Pillutla; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2022)

Influence Diagnostics under Self-concordance. - Jillian Fisher; Lang Liu; Krishna Pillutla; Yejin Choi 001; Zaïd Harchaoui (AISTATS, 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - Ximing Lu; Faeze Brahman; Peter West; Jaehun Jung; Khyathi Raghavi Chandu; Abhilasha Ravichander; Prithviraj Ammanabrolu; Liwei Jiang; Sahana Ramnath; Nouha Dziri; Jillian Fisher; Bill Y. Lin; et al. (EMNLP, 2023)

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 001 (CoRR, 2023)

Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration. - Shangbin Feng; Taylor Sorensen; Yuhan Liu; Jillian Fisher; Chan Young Park; Yejin Choi 001; Yulia Tsvetkov (EMNLP, 2024)

StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. - Jillian Fisher; Skyler Hallinan; Ximing Lu; Mitchell L. Gordon; Zaïd Harchaoui; Yejin Choi 001 (EMNLP, 2024)

The Generative AI Paradox: "What It Can Create, It May Not Understand". - Peter West; Ximing Lu; Nouha Dziri; Faeze Brahman; Linjie Li; Jena D. Hwang; Liwei Jiang; Jillian Fisher; Abhilasha Ravichander; Khyathi Raghavi Chandu; Benjamin Newman; Pang Wei Koh; et al. (ICLR, 2024)

Position: A Roadmap to Pluralistic Alignment. - Taylor Sorensen; Jared Moore; Jillian Fisher; Mitchell L. Gordon; Niloofar Mireshghallah; Christopher Michael Rytting; Andre Ye; Liwei Jiang; Ximing Lu; Nouha Dziri; Tim Althoff; Yejin Choi 001 (ICML, 2024)

JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. - Jillian Fisher; Ximing Lu; Jaehun Jung; Liwei Jiang; Zaïd Harchaoui; Yejin Choi 001 (NAACL-HLT, 2024)

Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model. - Jaehun Jung; Peter West; Liwei Jiang; Faeze Brahman; Ximing Lu; Jillian Fisher; Taylor Sorensen; Yejin Choi 001 (NAACL-HLT, 2024)

A Roadmap to Pluralistic Alignment. - Taylor Sorensen; Jared Moore; Jillian Fisher; Mitchell L. Gordon; Niloofar Mireshghallah; Christopher Michael Rytting; Andre Ye; Liwei Jiang; Ximing Lu; Nouha Dziri; Tim Althoff; Yejin Choi 001 (CoRR, 2024)

Biased AI can Influence Political Decision-Making. - Jillian Fisher; Shangbin Feng; Robert Aron; Thomas Richardson; Yejin Choi 001; Daniel W. Fisher; Jennifer Pan; Yulia Tsvetkov; Katharina Reinecke (CoRR, 2024)

Biased LLMs can Influence Political Decision-Making. - Jillian Fisher; Shangbin Feng; Robert Aron; Thomas Richardson; Yejin Choi; Daniel W. Fisher; Jennifer Pan; Yulia Tsvetkov; Katharina Reinecke (ACL (1), 2025)

Information-Guided Identification of Training Data Imprint in (Proprietary) Large Language Models. - Abhilasha Ravichander; Jillian Fisher; Taylor Sorensen; Ximing Lu; Maria Antoniak; Bill Yuchen Lin; Niloofar Mireshghallah; Chandra Bhagavatula; Yejin Choi 001 (NAACL (Long Papers), 2025)

Political Neutrality in AI is Impossible- But Here is How to Approximate it. - Jillian Fisher; Ruth E. Appel; Chan Young Park; Yujin Potter; Liwei Jiang; Taylor Sorensen; Shangbin Feng; Yulia Tsvetkov; Margaret E. Roberts; Jennifer Pan; Dawn Song; Yejin Choi 001 (CoRR, 2025)

Making VLMs More Robot-Friendly: Self-Critical Distillation of Low-Level Procedural Reasoning. - Chan Young Park; Jillian Fisher; Marius Memmel; Dipika Khullar; Seoho Yun; Abhishek Gupta; Yejin Choi (CoRR, 2025)