[{'Paper': 'Post-hoc Utterance Refining Method by Entity Mining for Faithful Knowledge Grounded Conversations', 'Authors': 'Yoonna Jang, Suhyune Son, Jeongwoo Lee, et al.', 'Conference': 'EMNLP 2023'}, {'Paper': 'Explore the Way: Exploring Reasoning Path by Bridging Entities for Effective Cross-Document Relation Extraction', 'Authors': 'Junyoung Son, Jinsung Kim, Jungwoo Lim, et al.', 'Conference': 'EMNLP 2023 Findings'}, {'Paper': 'Doubts on the reliability of parallel corpus filtering', 'Authors': 'Hyeonseok Moon, Chanjun Park, Seonmin Koo, et al.', 'Journal': 'Expert Systems with Applications 2023'}, {'Paper': 'PEEP-Talk: A Situational Dialogue-based Chatbot for English Education', 'Authors': 'Seugnjun Lee, Yoonna Jang, et al.', 'Conference': 'ACL 2023 Demo'}, {'Paper': 'You Truly Understand What I Need: Intellectual and Friendly Dialogue Agents grounding Knowledge and Persona', 'Authors': 'Jungwoo Lim, Myunghoon Kang, Yuna Hur, et al.', 'Conference': 'EMNLP 2022 Findings'}, {'Paper': 'PicTalky: Augmentative and Alternative Communication Software for Language Developmental Disabilities', 'Authors': 'Chanjun Park, Yoonna Jang, et al.', 'Conference': 'AACL-IJCNLP 2022 Demo'}, {'Paper': 'A Dog Is Passing Over The Jet? A Text-Generation Dataset for Korean Commonsense Reasoning and Evaluation', 'Authors': 'Jaehyung Seo, Seounghoon Lee, Chanjun Park, et al.', 'Conference': 'NAACL Findings 2022'}, {'Paper': 'FREETALKY: Don’t Be Afraid! Conversations Made Easier by a Humanoid Robot using Persona-based Dialogue', 'Authors': 'Chanjun Park, Yoonna Jang, et al.', 'Conference': 'LREC 2022'}, {'Paper': 'Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledge', 'Authors': 'Yoonna Jang, Jungwoo Lim, Yuna Hur, et al.', 'Conference': 'AAAI 2022'}, {'Paper': 'I Know What You Asked: Graph Path Learning using AMR for Commonsense Reasoning', 'Authors': 'Jungwoo Lim, Dongsuk Oh, Yoonna Jang, et al.', 'Conference': 'COLING 2020'}]
Background
NLP researcher, focusing on dialogue systems and commonsense reasoning. Current research interests lie in the factuality and explainability of language models, aiming to make AI models more beneficial to humans and society.