| 2025 | COLING | Making Task-Oriented Dialogue Datasets More Natural by Synthetically Generating Indirect User Requests. | Amogh Mannekote, Jinseok Nam, Ziming Li, Kristy Elizabeth Boyer, Bonnie J. Dorr |
| 2023 | ICCV | Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency. | Jungbeom Lee, Sungjin Lee, Jinseok Nam, Seunghak Yu, Jaeyoung Do, Tara Taghavi |
| 2022 | NAACL | Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems. | Mohammad Kachuee, Jinseok Nam, Sarthak Ahuja, Jin-Myung Won, Sungjin Lee |
| 2019 | ICML | Learning Context-dependent Label Permutations for Multi-label Classification. | Jinseok Nam, Young-Bum Kim, Eneldo Loza Menca, Sunghyun Park, Ruhi Sarikaya, Johannes Frnkranz |
| 2016 | AAAI | All-in Text: Learning Document, Label, and Word Representations Jointly. | Jinseok Nam, Eneldo Loza Menca, Johannes Frnkranz |
| 2016 | COLING | What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation. | Fabian Hirschmann, Jinseok Nam, Johannes Frnkranz |
| 2016 | ESANN | Using semantic similarity for multi-label zero-shot classification of text documents. | Prateek Veeranna Sappadla, Jinseok Nam, Eneldo Loza Menca, Johannes Frnkranz |
| 2016 | LREC | Medical Concept Embeddings via Labeled Background Corpora. | Eneldo Loza Menca, Gerard de Melo, Jinseok Nam |
| 2012 | COLING | Learning Semantics with Deep Belief Network for Cross-Language Information Retrieval. | Jungi Kim, Jinseok Nam, Iryna Gurevych |