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Hongsen Yu

3 accepted papers

2025

Entity Pair-guided Relation Summarization and Retrieval in LLMs for Document-level Relation Extraction

NAACL 2025findings

Document-level relation extraction (DocRE) aims to extract relations between entities in a document. While previous research has primarily focused on traditional small models, recent studies have extended the scope to large language models (LLMs). Current LLM-based methods typically focus on filteri…

2025

Rethinking the Role of LLMs for Document-level Relation Extraction: a Refiner with Task Distribution and Probability Fusion

NAACL 2025long

Document-level relation extraction (DocRE) provides a broad context for extracting one or more relations for each entity pair. Large language models (LLMs) have made great progress in relation extraction tasks. However, one of the main challenges we face is that LLMs have difficulty in multi-label r…

2024

SRF: Enhancing Document-Level Relation Extraction with a Novel Secondary Reasoning Framework

EMNLP 2024main

Document-level Relation Extraction (DocRE) aims to extract relations between entity pairs in a document and poses many challenges as it involves multiple mentions of entities and cross-sentence inference. However, several aspects that are important for DocRE have not been considered and explored. Ex…