5 papers
From Ambiguity to Accuracy: The Transformative Effect of Coreference Resolution on Retrieval-Augmented Generation systems
Youngjoon Jang, Seongtae Hong, Junyoung Son +3
Retrieval-Augmented Generation (RAG) has emerged as a crucial framework in natural language processing (NLP), improving factual consistency and reducing hallucinations by integrati…
Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing
Eunbyeol Cho, Jiyoun Kim, Minjae Lee +2
Electronic Health Records (EHR) are time-series relational databases that record patient interactions and medical events over time, serving as a critical resource for healthcare re…
Enhancing LLMs' Clinical Reasoning with Real-World Data from a Nationwide Sepsis Registry
Junu Kim, Chaeeun Shim, Sungjin Park +16
Although large language models (LLMs) have demonstrated impressive reasoning capabilities across general domains, their effectiveness in real-world clinical practice remains limite…
Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning
Sungjin Park, Xiao Liu, Yeyun Gong +1
Despite recent advances in large language models, open-source models often struggle to consistently perform well on complex reasoning tasks. Existing ensemble methods, whether appl…
Multimodal Transformer With a Low-Computational-Cost Guarantee
Sungjin Park, Edward Choi
Transformer-based models have significantly improved performance across a range of multimodal understanding tasks, such as visual question answering and action recognition. However…