| 2025 | COLING | The Role of Handling Attributive Nouns in Improving Chinese-To-English Machine Translation. | Adam Meyers, Rodolfo Joel Zevallos Salazar, John E. Ortega, Lisa Wang |
| 2025 | COLING | Is Peer-Reviewing Worth the Effort? | Kenneth Ward Church, Raman Chandrasekar, John E. Ortega, Ibrahim Said Ahmad |
| 2025 | COLING | Semantic Role Labeling of NomBank Partitives. | Adam Meyers, Advait Pravin Savant, John E. Ortega |
| 2025 | COLING | The First Multilingual Model For The Detection of Suicide Texts. | Rodolfo Joel Zevallos Salazar, Annika Marie Schoene, John E. Ortega |
| 2025 | COLING | Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language. | Annika Marie Schoene, John E. Ortega, Rodolfo Joel Zevallos Salazar, Laura Haaber Ihle |
| 2024 | AMTA | Predicting Anchored Text from Translation Memories for Machine Translation Using Deep Learning Methods. | Richard Yue, John E. Ortega |
| 2024 | AMTA | On Translating Technical Terminology: A Translation Workflow for Machine-Translated Acronyms. | Richard Yue, John E. Ortega, Kenneth Church |
| 2024 | COLING | Evaluating Self-Supervised Speech Representations for Indigenous American Languages. | Chih-Chen Chen, William Chen, Rodolfo Joel Zevallos Salazar, John E. Ortega |
| 2024 | COLING | Related Work Is All You Need. | Rodolfo Joel Zevallos Salazar, John E. Ortega, Benjamin Irving |
| 2023 | EACL | Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models. | Abteen Ebrahimi, Arya D. McCarthy, Arturo Oncevay, John E. Ortega, Luis Chiruzzo, Gustavo Gimnez Lugo, Rolando Coto-Solano, Katharina Kann |
| 2023 | ICWSM | An Example of (Too Much) Hyper-Parameter Tuning In Suicide Ideation Detection. | Annika Marie Schoene, John E. Ortega, Silvio Amir, Kenneth Church |
| 2023 | RANLP | A Research-Based Guide for the Creation and Deployment of a Low-Resource Machine Translation System. | John E. Ortega, Kenneth Church |
| 2023 | RANLP | Classification of US Supreme Court Cases Using BERT-Based Techniques. | Shubham Vatsal, Adam Meyers, John E. Ortega |
| 2022 | ACL | AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages. | Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, Vishrav Chaudhary, Luis Chiruzzo, Angela Fan, John E. Ortega, Ricardo Ramos, Annette Rios, Ivn Vladimir Meza Ruz, Gustavo Gimnez Lugo, Elisabeth Mager, Graham Neubig, Alexis Palmer, Rolando Coto-Solano, Ngoc Thang Vu, Katharina Kann |
| 2022 | COLING | WordNet-QU: Development of a Lexical Database for Quechua Varieties. | Nelsi Melgarejo, Rodolfo Zevallos, Hector Gomez, John E. Ortega |
| 2018 | AMTA | A Comparison of Machine Translation Paradigms for Use in Black-Box Fuzzy-Match Repair. | Rebecca Knowles, John E. Ortega, Philipp Koehn |
| 2018 | AMTA | Using Morphemes from Agglutinative Languages like Quechua and Finnish to Aid in Low-Resource Translation. | John E. Ortega, Krishnan Pillaipakkamnatt |
| 2018 | EAMT | Letting a Neural Network Decide Which Machine Translation System to Use for Black-Box Fuzzy-Match Repair. | John E. Ortega, Weiyi Lu, Adam Meyers, Kyunghyun Cho |
| 2018 | FedCSIS | A Comparative Study of Classifying Legal Documents with Neural Networks. | Samir Undavia, Adam Meyers, John E. Ortega |
| 2016 | AMTA | Fuzzy-match repair using black-box machine translation systems: what can be expected? | John E. Ortega, Felipe Snchez-Martnez, Mikel L. Forcada |
| 2014 | AMTA | Using any machine translation source for fuzzy-match repair in a computer-aided translation setting. | John E. Ortega, Felipe Snchez-Martnez, Mikel L. Forcada |