Papers by Ali Dabirmoghaddam
Finding Replicable Human Evaluations via Stable Ranking Probability (2024.naacl-long)
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| Challenge: | a recent study shows that human evaluation is the best way to rank natural language generation systems . human raters can exhibit different behaviors when rating outputs, causing ranking to be unstable . stability is the degree to which a specific evaluation methodology produces the same system ranking when repeated. |
| Approach: | They propose to evaluate results through the lens of stability: stability is the degree to which a specific evaluation methodology produces the same system ranking when repeated. |
| Outcome: | The proposed model is based on a dataset of multi-segment translations rated by multiple professionals . human raters can exhibit different behaviors when rating NLG outputs, the study shows . |
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents (2022.acl-long)
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| Challenge: | Document-level neural machine translation (DocNMT) is a powerful tool for integrating cross-sentence context into translations. |
| Approach: | They explore whether and how contextual modeling in DocNMT is transferable via multilingual modeling. |
| Outcome: | The proposed model can be used to transfer from teacher languages to student languages with no documents but sentence level data. |