Papers with argument role labeling

3 papers
Cross-media Structured Common Space for Multimedia Event Extraction (2020.acl-main)

Copied to clipboard

Challenge: We propose a new task to extract events and their arguments from multimedia documents . traditional methods target text, images or videos, but multimedia content is distributed via multimedia .
Approach: They propose a method that encodes structured representations of semantic information from textual and visual data into a common embedding space.
Outcome: The proposed method achieves 4.0% and 9.8% absolute gains on text event argument role labeling and visual event extraction.
An Empirical Study of Pre-trained Transformers for Arabic Information Extraction (2020.emnlp-main)

Copied to clipboard

Challenge: Multilingual pre-trained Transformers have been shown to enable effective cross-lingual zero-shot transfer, but their performance on Arabic information extraction tasks is not well studied.
Approach: They pre-train a bilingual BERT that is designed specifically for Arabic NLP and English-to-Arabic zero-shot transfer learning.
Outcome: The pre-trained model significantly outperforms mBERT, XLM-RoBERTa, and AraBERT in both the supervised and zero-shot transfer settings.
ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining (2022.coling-1)

Copied to clipboard

Challenge: Existing abstractive summarization models do not take into account argumentative structure of legal documents, which poses a challenge towards effective abstractive summary.
Approach: They propose a technique that integrates argument role labeling into the summarization process by integrating argument role labels into the document.
Outcome: The proposed method improves over strong baselines with pretrained language models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations