110 citations · 148 across the 9 of their papers we have counts for
10 papers
Qwen Technical Report
Jinze Bai, Shuai Bai, Yunfei Chu +45
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Keming Lu, Hongyi Yuan, Zheng Yuan +5
Foundation language models obtain the instruction-following ability through supervised fine-tuning (SFT). Diversity and complexity are considered critical factors of a successful S…
PIVOINE: Instruction Tuning for Open-world Information Extraction
Keming Lu, Xiaoman Pan, Kaiqiang Song +3
We consider the problem of Open-world Information Extraction (Open-world IE), which extracts comprehensive entity profiles from unstructured texts. Different from the conventional…
Exploring Partial Knowledge Base Inference in Biomedical Entity Linking
Hongyi Yuan, Keming Lu, Zheng Yuan
Biomedical entity linking (EL) consists of named entity recognition (NER) and named entity disambiguation (NED). EL models are trained on corpora labeled by a predefined KB. Howeve…
Multi-hop Evidence Retrieval for Cross-document Relation Extraction
Keming Lu, I-Hung Hsu, Wenxuan Zhou +2
Relation Extraction (RE) has been extended to cross-document scenarios because many relations are not simply described in a single document. This inevitably brings the challenge of…
Knowledge-Enhanced Relation Extraction Dataset
Yucong Lin, Hongming Xiao, Jiani Liu +4
Recently, knowledge-enhanced methods leveraging auxiliary knowledge graphs have emerged in relation extraction, surpassing traditional text-based approaches. However, to our best k…