Papers by Yiqing Shen
Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion (2022.findings-acl)
Copied to clipboard
| Challenge: | Document-level relation extraction (DocRE) aims to extract semantic relations among entity pairs in a document. |
| Approach: | They propose an evidence-enhanced framework that empowers document-level relation extraction (DocRE) Eider efficiently extracts evidence and effectively fuses extracted evidence in inference. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on three benchmark datasets. |
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering (2025.coling-industry)
Copied to clipboard
| Challenge: | Deep learning models are often inefficient and resource-intensive for biologists without specialized computational expertise. |
| Approach: | They propose an agent framework that leverages large language models for multimodal automated machine learning (AutoML) in protein engineering. |
| Outcome: | The proposed framework demonstrates significant improvements in performance over previous approaches in two real-world protein engineering tasks. |