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Attention mechanisms have seen some success for natural language processingdownstream tasks in recent years and generated new State-of-the-Art results. Athorough evaluation of the attention mechanism for the task of ArgumentationMining is missing, though. With this paper, we report a comparative evaluationof attention layers in combination with a bidirectional long short-term memorynetwork, which is the current state-of-the-art approach to the unitsegmentation task. We also compare sentence-level contextualized wordembeddings to pre-generated ones. Our findings suggest that for this task theadditional attention layer does not improve upon a less complex approach. Inmost cases, the contextualized embeddings do also not show an improvement onthe baseline score.

Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation