Web12 lug 2024 · argument mining citation context analysis computational social science cross-language information retrieval cross-lingual information retrieval data augmentation extreme multi-label knowledge discovery knowledge graph legal text mixup multi-task paraphrase passage ... with a particular focus on BERT. We find that BERT is sensitive … Web28 set 2024 · Cross-Topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks. arXiv preprint arXiv:1802.05758, pages 3664–3674. Steinhaus (1956) Hugo Steinhaus. 1956. Sur la division del corps matériels en parties. Technical Report 12. Trautmann (2024) Dietrich Trautmann. 2024. Aspect-based argument mining.
Multilingual Argument Mining: Datasets and Analysis
WebDebateSum consists of 187,386 unique pieces of evidence with corresponding argument and extractive summaries. DebateSum was made using data compiled by competitors within the National Speech and Debate Association over a 7-year period. We train several transformer summarization models to benchmark summarization performance on … Web7 apr 2024 · We compare different argument mining approaches and develop a generic model that can successfully detect argument structures in different datasets of mobility … how tall is harry potter in year 3
(PDF) Enhancing Legal Argument Mining with Domain Pre-training …
Web12 giu 2024 · Argument extraction is the core task of argument mining by identifying those parts of a document that are argumentative. We address this problem on two levels, on … Web13 ott 2024 · The growing interest in argument mining and computational argumentation brings with it a plethora of Natural Language Understanding (NLU) tasks and corresponding datasets. However, as with many other NLU tasks, the dominant language is English, with resources in other languages being few and far between. In this work, we explore the … WebPrevious work has demonstrated that end-to-end neural sequence models work well for document-level event role filler extraction. However, the end-to-end neural network model suffers from the problem of not being able to utilize global information, resulting in incomplete extraction of document-level event arguments. This is because the inputs to … how tall is harry prince of sussex