7 papers
Segment-level Tree Search for Long Meeting Document Summarization
Sangwon Ryu, Heejin Do, Jun Seo +4
Meeting documents are challenging to summarize due to their length and complex conversational structure. Existing approaches typically adopt multi-stage pipelines that extract info…
Exploring Iterative Controllable Summarization with Large Language Models
Sangwon Ryu, Heejin Do, Daehee Kim +5
Large language models (LLMs) have demonstrated remarkable performance in abstractive summarization tasks. However, their ability to precisely control summary attributes (e.g., leng…
DeRAGEC: Denoising Named Entity Candidates with Synthetic Rationale for ASR Error Correction
Solee Im, Wonjun Lee, Jinmyeong An +3
We present DeRAGEC, a method for improving Named Entity (NE) correction in Automatic Speech Recognition (ASR) systems. By extending the Retrieval-Augmented Generative Error Correct…
DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognition
Wonjun Lee, Solee Im, Heejin Do +3
Dysarthric speech recognition often suffers from performance degradation due to the intrinsic diversity of dysarthric severity and extrinsic disparity from normal speech. To bridge…
Key-Element-Informed sLLM Tuning for Document Summarization
Sangwon Ryu, Heejin Do, Yunsu Kim +2
Remarkable advances in large language models (LLMs) have enabled high-quality text summarization. However, this capability is currently accessible only through LLMs of substantial…
Cross-lingual Transfer for Automatic Question Generation by Learning Interrogative Structures in Target Languages
Seonjeong Hwang, Yunsu Kim, Gary Geunbae Lee
Automatic question generation (QG) serves a wide range of purposes, such as augmenting question-answering (QA) corpora, enhancing chatbot systems, and developing educational materi…