no code implementations • 12 Jul 2023 • Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee
This paper presents "Predictive Pipelined Decoding (PPD)," an approach that speeds up greedy decoding in Large Language Models (LLMs) while maintaining the exact same output as the original decoding.
1 code implementation • NeurIPS 2022 Datasets and Benchmarks 2022 • Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin, Seongjun Yang, Minjoon Seo, Jong-Yeup Kim, Edward Choi
We then manually linked these questions to two open-source EHR databases, MIMIC-III and eICU, and included various time expressions and held-out unanswerable questions in the dataset, which were also collected from the poll.
1 code implementation • 14 Nov 2022 • Junu Kim, Kyunghoon Hur, Seongjun Yang, Edward Choi
Federated learning (FL) is the most practical multi-source learning method for electronic healthcare records (EHR).
no code implementations • 26 Jul 2022 • Radhika Dua, Seongjun Yang, Yixuan Li, Edward Choi
Despite the recent advances in out-of-distribution(OOD) detection, anomaly detection, and uncertainty estimation tasks, there do not exist a task-agnostic and post-hoc approach.
1 code implementation • 7 Jul 2022 • Seongjun Yang, Hyeonji Hwang, Daeyoung Kim, Radhika Dua, Jong-Yeup Kim, Eunho Yang, Edward Choi
We evaluate six FL algorithms designed for addressing data heterogeneity among clients, and a hybrid algorithm combining the strengths of two representative FL algorithms.
1 code implementation • ACL 2021 • Gyubok Lee, Seongjun Yang, Edward Choi
Accurate terminology translation is crucial for ensuring the practicality and reliability of neural machine translation (NMT) systems.