Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. - Alexander Miserlis Hoyle; Lawrence Wolf-Sonkin; Hanna M. Wallach; Isabelle Augenstein; Ryan Cotterell (ACL (1), 2019)

Combining Sentiment Lexica with a Multi-View Variational Autoencoder. - Alexander Miserlis Hoyle; Lawrence Wolf-Sonkin; Hanna M. Wallach; Ryan Cotterell; Isabelle Augenstein (NAACL-HLT (1), 2019)

Improving Neural Topic Models using Knowledge Distillation. - Alexander Miserlis Hoyle; Pranav Goel 001; Philip Resnik (EMNLP (1), 2020)

Promoting Graph Awareness in Linearized Graph-to-Text Generation. - Alexander Miserlis Hoyle; Ana Marasovic; Noah A. Smith (ACL/IJCNLP (Findings), 2021)

Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? - Pedro Rodriguez 001; Joe Barrow; Alexander Miserlis Hoyle; John P. Lalor; Robin Jia; Jordan L. Boyd-Graber (ACL/IJCNLP (1), 2021)

Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence. - Alexander Miserlis Hoyle; Pranav Goel 001; Andrew Hian-Cheong; Denis Peskov; Jordan L. Boyd-Graber; Philip Resnik (NeurIPS, 2021)

Are Neural Topic Models Broken? - Alexander Miserlis Hoyle; Rupak Sarkar; Pranav Goel 001; Philip Resnik (EMNLP (Findings), 2022)

Natural Language Decompositions of Implicit Content Enable Better Text Representations. - Alexander Miserlis Hoyle; Rupak Sarkar; Pranav Goel 001; Philip Resnik (EMNLP, 2023)

Revisiting Automated Topic Model Evaluation with Large Language Models. - Dominik Stammbach; Vilém Zouhar; Alexander Miserlis Hoyle; Mrinmaya Sachan; Elliott Ash (EMNLP, 2023)

Re-visiting Automated Topic Model Evaluation with Large Language Models. - Dominik Stammbach; Vilém Zouhar; Alexander Miserlis Hoyle; Mrinmaya Sachan; Elliott Ash (CoRR, 2023)

Making the Implicit Explicit: Implicit Content as a First Class Citizen in NLP. - Alexander Miserlis Hoyle; Rupak Sarkar; Pranav Goel 001; Philip Resnik (CoRR, 2023)

TopicGPT: A Prompt-based Topic Modeling Framework. - Chau Minh Pham; Alexander Miserlis Hoyle; Simeng Sun; Mohit Iyyer (CoRR, 2023)

A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick. - Nishant Balepur; Matthew Shu; Alexander Miserlis Hoyle; Alison Robey; Shi Feng 005; Seraphina Goldfarb-Tarrant; Jordan L. Boyd-Graber (EMNLP, 2024)

TopicGPT: A Prompt-based Topic Modeling Framework. - Chau Pham; Alexander Miserlis Hoyle; Simeng Sun; Philip Resnik; Mohit Iyyer (NAACL-HLT, 2024)

The Prompt Report: A Systematic Survey of Prompting Techniques. - Sander Schulhoff; Michael Ilie; Nishant Balepur; Konstantine Kahadze; Amanda Liu; Chenglei Si; Yinheng Li; Aayush Gupta; HyoJung Han; Sevien Schulhoff; Pranav Sandeep Dulepet; Saurav Vidyadhara; et al. (CoRR, 2024)

ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering. - Alexander Miserlis Hoyle; Lorena Calvo-Bartolomé; Jordan Lee Boyd-Graber; Philip Resnik (ACL (1), 2025)

Large Language Models Struggle to Describe the Haystack without Human Help: A Social Science-Inspired Evaluation of Topic Models. - Zongxia Li; Lorena Calvo-Bartolomé; Alexander Miserlis Hoyle; Paiheng Xu; Daniel Kofi Stephens; Juan Francisco Fung; Alden Dima; Jordan Lee Boyd-Graber (ACL (1), 2025)

PairScale: Analyzing Attitude Change with Pairwise Comparisons. - Rupak Sarkar; Patrick Y. Wu; Kristina Miler; Alexander Miserlis Hoyle; Philip Resnik (NAACL (Findings), 2025)

Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of LLMs. - Zongxia Li; Lorena Calvo-Bartolomé; Alexander Miserlis Hoyle; Paiheng Xu; Alden Dima; Juan Francisco Fung; Jordan L. Boyd-Graber (CoRR, 2025)

Can Large Language Models Capture Human Annotator Disagreements? - Jingwei Ni; Yu Fan; Vilém Zouhar; Donya Rooein; Alexander Miserlis Hoyle; Mrinmaya Sachan; Markus Leippold; Dirk Hovy; Elliott Ash (CoRR, 2025)

The Medium Is Not the Message: Deconfounding Text Embeddings via Linear Concept Erasure. - Yu Fan; Yang Tian; Shauli Ravfogel; Mrinmaya Sachan; Elliott Ash; Alexander Miserlis Hoyle (CoRR, 2025)

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification. - Chenfei Xiong; Jingwei Ni; Yu Fan; Vilém Zouhar; Donya Rooein; Lorena Calvo-Bartolomé; Alexander Miserlis Hoyle; Zhijing Jin 001; Mrinmaya Sachan; Markus Leippold; Dirk Hovy; Mennatallah El-Assady; et al. (CoRR, 2025)