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arXiv · 2006.03773

Challenges and Thrills of Legal Arguments

Anurag Pallaprolu·Radha Vaidya·Aditya Swaroop Attawar
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Abstract

State-of-the-art attention based models, mostly centered around the transformer architecture, solve the problem of sequence-to-sequence translation using the so-called scaled dot-product attention. While this technique is highly effective for estimating inter-token attention, it does not answer the question of inter-sequence attention when we deal with conversation-like scenarios. We propose an extension, HumBERT, that attempts to perform continuous contextual argument generation using locally trained transformers.

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Anurag Pallaprolu, Radha Vaidya, Aditya Swaroop Attawar. 2020-06-06. Challenges and Thrills of Legal Arguments. https://arxiv.org/abs/2006.03773

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