Papers with cross-sentence inference

3 papers
R2F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference (2022.emnlp-main)

Copied to clipboard

Challenge: Document-level natural language inference (DOCNLI) is a new task in natural language processing.
Approach: They propose a document-level natural language inference framework that fuses sentence-level tasks into a set of sentence-based tasks.
Outcome: The proposed framework improves interpretability and performance with evidence.
Enhancing Document-level Event Argument Extraction with Contextual Clues and Role Relevance (2023.findings-acl)

Copied to clipboard

Challenge: Document-level event argument extraction is a challenging task for cross-sentence inference . previous work focused on document-level EAE, but recent work focused more on documentlevel .
Approach: They propose a document-level event argument extraction model that captures contextual clues and latent role information.
Outcome: The proposed model outperforms existing methods on two public datasets with 1.13 F1 and 2.64 F1 improvements on RAMS and WikiEvents respectively.
SRF: Enhancing Document-Level Relation Extraction with a Novel Secondary Reasoning Framework (2024.emnlp-main)

Copied to clipboard

Challenge: Existing methods for document-level relation extraction ignore bidirectional mention interaction when generating relational features for entity pairs.
Approach: They propose a document-level relation extraction model that incorporates bidirectional mention fusion and a simple yet effective evidence extraction module for relation prediction.
Outcome: The proposed model achieves SOTA performance and the proposed method is effective and general when integrated into existing 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