20 citations · 20 across the 5 of their papers we have counts for
5 papers
KU-DMIS at EHRSQL 2024:Generating SQL query via question templatization in EHR
Hajung Kim, Chanhwi Kim, Hoonick Lee +5
Transforming natural language questions into SQL queries is crucial for precise data retrieval from electronic health record (EHR) databases. A significant challenge in this proces…
PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering
Wookje Han, Jinsol Park, Kyungjae Lee
Information-seeking questions in long-form question answering (LFQA) often prove misleading due to ambiguity or false presupposition in the question. While many existing approaches…
On Monotonic Aggregation for Open-domain QA
Sang-eun Han, Yeonseok Jeong, Seung-won Hwang +1
Question answering (QA) is a critical task for speech-based retrieval from knowledge sources, by sifting only the answers without requiring to read supporting documents. Specifical…
When to Read Documents or QA History: On Unified and Selective Open-domain QA
Kyungjae Lee, Sang-eun Han, Seung-won Hwang +1
This paper studies the problem of open-domain question answering, with the aim of answering a diverse range of questions leveraging knowledge resources. Two types of sources, QA-pa…
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Joel Jang, Seungone Kim, Seonghyeon Ye +5
Recently, Language Models (LMs) instruction-tuned on multiple tasks, also known as multitask-prompted fine-tuning (MT), have shown the capability to generalize to unseen tasks. Pre…