Seeded Discovery of Base Relations in Large Corpora. - Nicholas Andrews; Naren Ramakrishnan (EMNLP, 2008)

Name Phylogeny: A Generative Model of String Variation. - Nicholas Andrews; Jason Eisner; Mark Dredze (EMNLP-CoNLL, 2012)

Entity Clustering Across Languages. - Spence Green; Nicholas Andrews; Matthew R. Gormley; Mark Dredze; Christopher D. Manning (HLT-NAACL, 2012)

PARMA: A Predicate Argument Aligner. - Travis Wolfe; Benjamin Van Durme; Mark Dredze; Nicholas Andrews; Charley Beller; Chris Callison-Burch; Jay DeYoung; Justin Snyder; Jonathan Weese; Tan Xu; Xuchen Yao (ACL (2), 2013)

Robust Entity Clustering via Phylogenetic Inference. - Nicholas Andrews; Jason Eisner; Mark Dredze (ACL (1), 2014)

A Concrete Chinese NLP Pipeline. - Nanyun Peng 001; Francis Ferraro; Mo Yu; Nicholas Andrews; Jay DeYoung; Max Thomas; Matthew R. Gormley; Travis Wolfe; Craig Harman; Benjamin Van Durme; Mark Dredze (HLT-NAACL, 2015)

Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation. - Mark Dredze; Nicholas Andrews; Jay DeYoung (SocialNLP@EMNLP, 2016)

Bayesian Modeling of Lexical Resources for Low-Resource Settings. - Nicholas Andrews; Mark Dredze; Benjamin Van Durme; Jason Eisner (ACL (1), 2017)

Predicting Twitter User Demographics from Names Alone. - Zach Wood-Doughty; Nicholas Andrews; Rebecca Marvin; Mark Dredze (PEOPLES@NAACL-HTL, 2018)

Convolutions Are All You Need (For Classifying Character Sequences). - Zach Wood-Doughty; Nicholas Andrews; Mark Dredze (NUT@EMNLP, 2018)

Learning Invariant Representations of Social Media Users. - Nicholas Andrews; Marcus Bishop (EMNLP/IJCNLP (1), 2019)

Sources of Transfer in Multilingual Named Entity Recognition. - David Mueller; Nicholas Andrews; Mark Dredze (ACL, 2020)

Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast - Choose Three. - Steven Reich; David Mueller; Nicholas Andrews (EMNLP (1), 2020)

Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning. - Mitchell A. Gordon; Kevin Duh; Nicholas Andrews (RepL4NLP@ACL, 2020)

Learning Universal Authorship Representations. - Rafael A. Rivera Soto; Olivia Elizabeth Miano; Juanita Ordonez; Barry Y. Chen; Aleem Khan; Marcus Bishop; Nicholas Andrews (EMNLP (1), 2021)

A Deep Metric Learning Approach to Account Linking. - Aleem Khan; Elizabeth Fleming; Noah Schofield; Marcus Bishop; Nicholas Andrews (NAACL-HLT, 2021)

Do Text-to-Text Multi-Task Learners Suffer from Task Conflict? - David Mueller; Nicholas Andrews; Mark Dredze (EMNLP (Findings), 2022)

Low-Resource Authorship Style Transfer with In-Context Learning. - Ajay Patel; Nicholas Andrews; Chris Callison-Burch (CoRR, 2022)

Forecasting Earnings Surprises from Conference Call Transcripts. - Ross Koval; Nicholas Andrews; Xifeng Yan (ACL (Findings), 2023)

Learning to Generate Text in Arbitrary Writing Styles. - Aleem Khan; Andrew Wang; Sophia Hager; Nicholas Andrews (CoRR, 2023)

Can Authorship Representation Learning Capture Stylistic Features? - Andrew Wang; Cristina Aggazzotti; Rebecca Kotula; Rafael A. Rivera Soto; Marcus Bishop; Nicholas Andrews (Trans. Assoc. Comput. Linguistics, 2023)

Multi-Task Transfer Matters During Instruction-Tuning. - David Mueller; Mark Dredze; Nicholas Andrews (ACL (Findings), 2024)

Learning to Compare Financial Reports for Financial Forecasting. - Ross Koval; Nicholas Andrews; Xifeng Yan (EACL (Findings), 2024)

Financial Forecasting from Textual and Tabular Time Series. - Ross Koval; Nicholas Andrews; Xifeng Yan (EMNLP (Findings), 2024)

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies. - Xiao Ye; Andrew Wang; Jacob Choi; Yining Lu; Shreya Sharma; Lingfeng Shen; Vijay Murari Tiyyala; Nicholas Andrews; Daniel Khashabi (EMNLP, 2024)

Few-Shot Detection of Machine-Generated Text using Style Representations. - Rafael A. Rivera Soto; Kailin Koch; Aleem Khan; Barry Y. Chen; Marcus Bishop; Nicholas Andrews (ICLR, 2024)

Privacy Versus Emotion Preservation Trade-Offs in Emotion-Preserving Speaker Anonymization. - Zexin Cai; Henry Li Xinyuan; Ashi Garg; Leibny Paola García-Perera; Kevin Duh; Sanjeev Khudanpur; Nicholas Andrews; Matthew Wiesner (SLT, 2024)

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies. - Xiao Ye; Andrew Wang; Jacob Choi; Yining Lu; Shreya Sharma 010; Lingfeng Shen; Vijay Murari Tiyyala; Nicholas Andrews; Daniel Khashabi (CoRR, 2024)

HLTCOE JHU Submission to the Voice Privacy Challenge 2024. - Henry Li Xinyuan; Zexin Cai; Ashi Garg; Kevin Duh; Leibny Paola García-Perera; Sanjeev Khudanpur; Nicholas Andrews; Matthew Wiesner (CoRR, 2024)

Are Paraphrases Generated by Large Language Models Invertible? - Rafael A. Rivera Soto; Barry Y. Chen; Nicholas Andrews (CoRR, 2024)

Can Authorship Attribution Models Distinguish Speakers in Speech Transcripts? - Cristina Aggazzotti; Nicholas Andrews; Elizabeth Allyn Smith (Trans. Assoc. Comput. Linguistics, 2024)

Mitigating Paraphrase Attacks on Machine-Text Detection via Paraphrase Inversion. - Rafael Alberto Rivera Soto; Barry Y. Chen; Nicholas Andrews (ACL (Findings), 2025)

HLTCOE Submission to the VoicePrivacy Attacker Challenge. - Henry Li Xinyuan; Ashi Garg; Zexin Cai; Kevin Duh; Leibny Paola García-Perera; Sanjeev Khudanpur; Nicholas Andrews; Matthew Wiesner (ICASSP, 2025)

Can Optimization Trajectories Explain Multi-Task Transfer? - David Mueller; Mark Dredze; Nicholas Andrews (Trans. Mach. Learn. Res., 2025)

GenVC: Self-Supervised Zero-Shot Voice Conversion. - Zexin Cai; Henry Li Xinyuan; Ashi Garg; Leibny Paola García-Perera; Kevin Duh; Sanjeev Khudanpur; Matthew Wiesner; Nicholas Andrews (CoRR, 2025)

Less is More for Synthetic Speech Detection in the Wild. - Ashi Garg; Zexin Cai; Henry Li Xinyuan; Leibny Paola García-Perera; Kevin Duh; Sanjeev Khudanpur; Matthew Wiesner; Nicholas Andrews (CoRR, 2025)

Uncertainty Distillation: Teaching Language Models to Express Semantic Confidence. - Sophia Hager; David Mueller; Kevin Duh; Nicholas Andrews (CoRR, 2025)

Language Models Optimized to Fool Detectors Still Have a Distinct Style (And How to Change It). - Rafael A. Rivera Soto; Barry Y. Chen; Nicholas Andrews (CoRR, 2025)

Learning Extrapolative Sequence Transformations from Markov Chains. - Sophia Hager; Aleem Khan; Andrew Wang; Nicholas Andrews (CoRR, 2025)

Feedback Friction: LLMs Struggle to Fully Incorporate External Feedback. - Dongwei Jiang; Alvin Zhang; Andrew Wang; Nicholas Andrews; Daniel Khashabi (CoRR, 2025)

The Impact of Automatic Speech Transcription on Speaker Attribution. - Cristina Aggazzotti; Matthew Wiesner; Elizabeth Allyn Smith; Nicholas Andrews (CoRR, 2025)

Hell or High Water: Evaluating Agentic Recovery from External Failures. - Andrew Wang; Sophia Hager; Adi Asija; Daniel Khashabi; Nicholas Andrews (CoRR, 2025)