1 citations · 1 across the 5 of their papers we have counts for
5 papers
Taming the Real-world Complexities in CPT E/M Coding with Large Language Models
Islam Nassar, Yang Lin, Yuan Jin +8
Evaluation and Management (E/M) coding, under the Current Procedural Terminology (CPT) taxonomy, documents medical services provided to patients by physicians. Used primarily for b…
FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation
Yulia Otmakhova, Hung Thinh Truong, Rahmad Mahendra +4
We present FLUKE (Framework for LingUistically-driven and tasK-agnostic robustness Evaluation), a framework for assessing model robustness through systematic minimal variations of…
Factual Dialogue Summarization via Learning from Large Language Models
Rongxin Zhu, Jey Han Lau, Jianzhong Qi
Factual consistency is an important quality in dialogue summarization. Large language model (LLM)-based automatic text summarization models generate more factually consistent summa…
Annotating and Detecting Fine-grained Factual Errors for Dialogue Summarization
Rongxin Zhu, Jianzhong Qi, Jey Han Lau
A series of datasets and models have been proposed for summaries generated for well-formatted documents such as news articles. Dialogue summaries, however, have been under explored…
Findings on Conversation Disentanglement
Rongxin Zhu, Jey Han Lau, Jianzhong Qi
Conversation disentanglement, the task to identify separate threads in conversations, is an important pre-processing step in multi-party conversational NLP applications such as con…