Papers by Yibin Yan
What Does Infect Mean to Cardio? Investigating the Role of Clinical Specialty Data in Medical LLMs (2026.eacl-long)
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| Challenge: | S-MedQA is an English question-answering dataset designed for benchmarking large language models in fine-grained clinical specialties. |
| Approach: | They propose to use an English medical question-answering dataset to benchmark large language models in clinical specialties. |
| Outcome: | The proposed dataset is designed to benchmark large language models in medical specialties. |
EchoSight: Advancing Visual-Language Models with Wiki Knowledge (2024.findings-emnlp)
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| Challenge: | Existing knowledge-based visual question answering systems struggle with these tasks due to limited integration of external knowledge. |
| Approach: | They propose a framework that enables large language models to answer visual questions requiring encyclopedic knowledge. |
| Outcome: | The proposed framework improves retrieval outcomes and accuracy of knowledge-based visual question answering tasks. |
SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generation (2024.emnlp-main)
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| Challenge: | Existing methods for enhancing RAG performance rely on heuristic-based augmentation . Existing approaches rely heavily on a heuriistic-driven approach, resulting in poor generalization and skews in the evidence length. |
| Approach: | They propose a model-based evidence extraction learning framework that optimizes a vanilla model as an evidence extractor with desired properties through self-aligned learning. |
| Outcome: | The proposed method reduces the evidence length by 9.25 times and improves reliability and reliability. |
War of Thoughts: Competition Stimulates Stronger Reasoning in Large Language Models (2025.findings-acl)
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| Challenge: | Recent advances in Large Language Models (LLMs) have reshaped the landscape of reasoning tasks. |
| Approach: | They propose a method that enhances LLM reasoning without finetuning by using test-time scaling. |
| Outcome: | The proposed method outperforms baseline models in both budget and model size. |