Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation. - Seraphina Goldfarb-Tarrant; Haining Feng; Nanyun Peng 001 (NAACL-HLT (Demonstrations), 2019)

Content Planning for Neural Story Generation with Aristotelian Rescoring. - Seraphina Goldfarb-Tarrant; Tuhin Chakrabarty; Ralph M. Weischedel; Nanyun Peng 001 (EMNLP (1), 2020)

Scaling Systematic Literature Reviews with Machine Learning Pipelines. - Seraphina Goldfarb-Tarrant; Alexander Robertson; Jasmina Lazic; Theodora Tsouloufi; Louise Donnison; Karen Smyth (SDP@EMNLP, 2020)

Intrinsic Bias Metrics Do Not Correlate with Application Bias. - Seraphina Goldfarb-Tarrant; Rebecca Marchant; Ricardo Muñoz Sánchez; Mugdha Pandya; Adam Lopez (ACL/IJCNLP (1), 2021)

How Gender Debiasing Affects Internal Model Representations, and Why It Matters. - Hadas Orgad; Seraphina Goldfarb-Tarrant; Yonatan Belinkov (NAACL-HLT, 2022)

This prompt is measuring extlessmask textgreater: evaluating bias evaluation in language models. - Seraphina Goldfarb-Tarrant; Eddie Ungless; Esma Balkir; Su Lin Blodgett (ACL (Findings), 2023)

Bias Beyond English: Counterfactual Tests for Bias in Sentiment Analysis in Four Languages. - Seraphina Goldfarb-Tarrant; Adam Lopez; Roi Blanco; Diego Marcheggiani (ACL (Findings), 2023)

Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis. - Seraphina Goldfarb-Tarrant; Björn Ross; Adam Lopez (EMNLP, 2023)

This Prompt is Measuring : Evaluating Bias Evaluation in Language Models. - Seraphina Goldfarb-Tarrant; Eddie Ungless; Esma Balkir; Su Lin Blodgett (CoRR, 2023)

The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm. - Aakanksha; Arash Ahmadian; Beyza Ermis; Seraphina Goldfarb-Tarrant; Julia Kreutzer; Marzieh Fadaee; Sara Hooker (EMNLP, 2024)

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)

MultiContrievers: Analysis of Dense Retrieval Representations. - Seraphina Goldfarb-Tarrant; Pedro Rodriguez 001; Jane Dwivedi-Yu; Patrick S. H. Lewis (CoRR, 2024)

Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning. - Aakanksha; Arash Ahmadian; Seraphina Goldfarb-Tarrant; Beyza Ermis; Marzieh Fadaee; Sara Hooker (CoRR, 2024)

Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to Artifacts. - Hongyu Chen 008; Seraphina Goldfarb-Tarrant (ACL (1), 2025)

Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring Contexts. - Preethi Seshadri; Seraphina Goldfarb-Tarrant (CoRR, 2025)

Command A: An Enterprise-Ready Large Language Model. - Aakanksha; Arash Ahmadian; Marwan Ahmed; Jay Alammar; Milad Alizadeh; Yazeed Alnumay; Sophia Althammer; Arkady Arkhangorodsky; Viraat Aryabumi; Dennis Aumiller; Raphaël Avalos; Zahara Aviv; et al. (CoRR, 2025)

MAPS: A Multilingual Benchmark for Global Agent Performance and Security. - Omer Hofman; Oren Rachmil; Shamik Bose; Vikas Pahuja; Jonathan Brokman; Toshiya Shimizu; Trisha Starostina; Kelly Marchisio; Seraphina Goldfarb-Tarrant; Roman Vainshtein (CoRR, 2025)

The Multilingual Divide and Its Impact on Global AI Safety. - Aidan Peppin; Julia Kreutzer; Alice Schoenauer Sebag; Kelly Marchisio; Beyza Ermis; John Dang; Samuel Cahyawijaya; Shivalika Singh; Seraphina Goldfarb-Tarrant; Viraat Aryabumi; Aakanksha; Wei-Yin Ko; et al. (CoRR, 2025)

Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them. - Neel Rajani; Aryo Pradipta Gema; Seraphina Goldfarb-Tarrant; Ivan Titov (CoRR, 2025)