Papers by Josef Genabith
MMAR: Multilingual and Multimodal Anaphora Resolution in Instructional Videos (2024.findings-emnlp)
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| Challenge: | Existing approaches to multilingual anaphora resolution include images and video inputs. |
| Approach: | They propose to include multimodal information in the form of images in anaphora resolution tasks. |
| Outcome: | The proposed approach improves resolution by 10% for unseen languages. |
To Clarify or not to Clarify: A Comparative Analysis of Clarification Classification with Fine-Tuning, Prompt Tuning, and Prompt Engineering (2024.naacl-srw)
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| Challenge: | Xu et al., 2019) show that pre-trained language model fine-tuning and prompt tuning are better than manual prompt engineering for clarification identification. |
| Approach: | They propose to use pre-trained language model fine-tuning, prompt tuning and manual prompt engineering to model clarification identification. |
| Outcome: | The proposed model outperforms pre-trained language model fine-tuning, prompt tuning and manual prompt engineering on the task of clarification identification. |
Towards Debiasing Translation Artifacts (2022.naacl-main)
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| Challenge: | Existing studies show translation artifacts in translations influence performance of cross-lingual tasks. |
| Approach: | They propose a method to reduce translation artifacts by extending an established bias-removal technique. |
| Outcome: | The proposed method reduces translationese at sentence and word level . it is the first study to debias translations on a natural language inference task . |
Sign Language Translation with Sentence Embedding Supervision (2024.acl-short)
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| Challenge: | State-of-the-art sign language translation systems facilitate learning through gloss annotations when available at scale. |
| Approach: | They propose to use sentence embeddings of the target sentences at training time that take the role of glosses to supervise the learning process. |
| Outcome: | The proposed method significantly outperforms gloss-free approaches on German and American sign languages and with mono- and multilingual sentence embeddings and translation systems. |