Papers with Dialogue-based relation extraction

2 papers
Graph Based Network with Contextualized Representations of Turns in Dialogue (2021.emnlp-main)

Copied to clipboard

Challenge: Dialogue-based relation extraction (RE) aims to extract relation(s) between two arguments that appear in a dialogue.
Approach: They propose a dialogue-based relation extraction model which is based on emotion recognition in conversations.
Outcome: The proposed model outperforms the state-of-the-art models on most of the benchmark datasets.
Knowledge-enhanced Prompt Tuning for Dialogue-based Relation Extraction with Trigger and Label Semantic (2024.lrec-main)

Copied to clipboard

Challenge: Existing methods to determine semantic relation between two arguments in dialogues are limited due to the low information density of text.
Approach: They propose a Knowledge-Enhanced Prompt-Tuning method to enhance DRE model by exploiting trigger and label semantics.
Outcome: The proposed method achieves state-of-the-art in F1 and F1c scores on a DialogRE dataset.

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