EMNLP 2024

Four papers from Emory NLP are presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP) 2024:

1. Diverse and Effective Synthetic Data Generation for Adaptable Zero-Shot Dialogue State Tracking. James D. Finch, Jinho D. Choi.
2. Identifying Factual Inconsistencies in Summaries: Grounding Model Inference via Task Taxonomy. Liyan Xu, Zhenlin Su, Mo Yu, Jin Xu, Jinho D. Choi, Jie Zhou, Fei Liu.
3. RRADistill: Distilling LLMs’ Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine. Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho, Haeyu Jeong, Jungmin Kong, Saehun Kim, Keunchan Park, Sarah Cho, Inchang Jeong, Gyohee Nam, Sunghoon Han, Wonil Yang, Jaeho Choi.
4. SLM as Guardian: Pioneering AI Safety with Small Language Model. Ohjoon Kwon, Donghyeon Jeon, Nayoung Choi, Gyu-Hwung Cho, Hwiyeol Jo, Changbong Kim, Hyunwoo Lee, Inho Kang, Sun Kim, Taiwoo Park.