Lightweight Connective Detection Using Gradient Boosting

arXiv:2404.13793v1 Announce Type: new
Abstract: In this work, we introduce a lightweight discourse connective detection system. Employing gradient boosting trained on straightforward, low-complexity features, this proposed approach sidesteps the computational demands of the current approaches that rely on deep neural networks. Considering its simplicity, our approach achieves competitive results while offering significant gains in terms of time even on CPU. Furthermore, the stable performance across two unrelated languages suggests the robustness of our system in the multilingual scenario. The model …

abstract arxiv boosting complexity computational cs.cl current detection discourse features gradient low networks neural networks results simplicity type work