Papers with Span extraction

2 papers
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension (2020.aacl-main)

Copied to clipboard

Challenge: Existing methods to predict the start and end positions of answer spans generate two probability vectors.
Approach: They propose a method that extends the probability vector to a probability matrix.
Outcome: The proposed method improves on SQuAD 1.1 and three other question answering benchmarks.
Enhanced Language Representation with Label Knowledge for Span Extraction (2021.emnlp-main)

Copied to clipboard

Challenge: Existing approaches to extract text spans from plain text do not fully exploit label knowledge.
Approach: They propose a model to integrate label knowledge into text representations by encoding texts and annotations independently and then integrating label knowledge with an elaborate-designed semantics fusion module.
Outcome: The proposed model achieves state-of-the-art performance on four benchmarks and reduces training time and inference time by 76% and 77% on average compared with the existing paradigm.

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