Papers by Marianna J. Martindale
Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection (2023.tacl-1)
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| Challenge: | Neural sequence generation models produce outputs that are unrelated to the source text, and are potentially harmful, yet it remains unclear in what conditions they arise and how to mitigate their impact. |
| Approach: | They first identify internal model symptoms of hallucinations by analyzing the relative token contributions to the generation in contrastive hallucinous vs. non-hallucinated outputs generated via source perturbations. |
| Outcome: | The proposed detector outperforms both baseline models and strong classifiers on English-Chinese and German-English translation test beds. |
Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations (2025.emnlp-main)
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Yimin Xiao, Yongle Zhang, Dayeon Ki, Calvin Bao, Marianna J. Martindale, Charlotte Vaughn, Ge Gao, Marine Carpuat
| Challenge: | Using machine translation tools for everyday tasks is becoming more commonplace, but a lack of evaluation strategies and alternatives can cause users to over-rely on it. |
| Approach: | They propose to use MT evaluation techniques to promote MT quality and MT literacy among its users. |
| Outcome: | The findings highlight the need for evaluation and NLP explanation techniques to promote MT quality and MT literacy among its users. |