most citedWord-Level ASR Quality Estimation for Efficient Corpus Sampling and Post-Editing through Analyzing Attentions of a Reference-Free Metric

1 citations · 2 across the 7 of their papers we have counts for

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7 papers

cs.CL2024

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…

cs.CL2024

Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic Parsing

Deokhyung Kang, Seonjeong Hwang, Yunsu Kim +1

Recent efforts have aimed to utilize multilingual pretrained language models (mPLMs) to extend semantic parsing (SP) across multiple languages without requiring extensive annotatio…

cs.CL2024

AutoMode-ASR: Learning to Select ASR Systems for Better Quality and Cost

Ahmet Gündüz, Yunsu Kim, Kamer Ali Yuksel +3

We present AutoMode-ASR, a novel framework that effectively integrates multiple ASR systems to enhance the overall transcription quality while optimizing cost. The idea is to train…

cs.CL2024

Explainable Multi-hop Question Generation: An End-to-End Approach without Intermediate Question Labeling

Seonjeong Hwang, Yunsu Kim, Gary Geunbae Lee

In response to the increasing use of interactive artificial intelligence, the demand for the capacity to handle complex questions has increased. Multi-hop question generation aims…

cs.CL2024

Denoising Table-Text Retrieval for Open-Domain Question Answering

Deokhyung Kang, Baikjin Jung, Yunsu Kim +1

In table-text open-domain question answering, a retriever system retrieves relevant evidence from tables and text to answer questions. Previous studies in table-text open-domain qu…

cs.CL20241 cited

Autoregressive Score Generation for Multi-trait Essay Scoring

Heejin Do, Yunsu Kim, Gary Geunbae Lee

Recently, encoder-only pre-trained models such as BERT have been successfully applied in automated essay scoring (AES) to predict a single overall score. However, studies have yet…