Anuranjana, Kaveri
DiscoFlan: Instruction Fine-tuning and Refined Text Generation for Discourse Relation Label Classificatio
Braud, Chloé; Janet Liu, Yang; Metheniti, Eleni; Muller, Philippe; Rivière, Laura; Rutherford, Attapol; Zeldes, Amir (Ed.): Proceedings of the 3rd Shared Task on Discourse Relation Parsing and Treebanking (DISRPT 2023), The Association for Computational Linguistics, pp. 22-28, Toronto, Canada, 2023.
This paper introduces DiscoFlan, a multilingual discourse relation classifier submitted for DISRPT 2023. Our submission represents the first attempt at building a multilingual discourse relation classifier for the DISRPT 2023 shared task. By our model addresses the issue to mismatches caused by hallucination in a seq2seq model by utilizing the label distribution information for label generation. In contrast to the previous state-of-the-art model, our approach eliminates the need for hand-crafted features in computing the discourse relation classes. Furthermore, we propose a novel label generation mechanism that anchors the labels to a fixed set by selectively enhancing training on the decoder model. Our experimental results demonstrate that our model surpasses the current state-of-the-art performance in 11 out of the 26 datasets considered, however the submitted model compatible with provided evaluation scripts is better in 7 out of 26 considered datasets, while demonstrating competitive results in the rest. Overall, DiscoFlan showcases promising advancements in multilingual discourse relation classification for the DISRPT 2023 shared task.