| A dataset of peer reviews (peerread): Collection, insights and nlp applications D Kang, W Ammar, B Dalvi, M van Zuylen, S Kohlmeier, E Hovy, ... NAACL 2018, 2018 | 235 | 2018 |
| INSPIRED: Toward Sociable Recommendation Dialog Systems S Anugrah Hayati, D Kang, Q Zhu, W Shi, Z Yu Empirical Methods in Natural Language Processing (EMNLP), arXiv: 2009.14306, 2020 | 144* | 2020 |
| Recommendation as a communication game: Self-supervised bot-play for goal-oriented dialogue D Kang, A Balakrishnan, P Shah, P Crook, YL Boureau, J Weston Empirical Methods in Natural Language Processing (EMNLP), 2019 | 126 | 2019 |
| Adventure: Adversarial training for textual entailment with knowledge-guided examples D Kang, T Khot, A Sabharwal, E Hovy Annual Meeting of the Association for Computational Linguistics (ACL), 2018 | 107 | 2018 |
| Augmenting scientific papers with just-in-time, position-sensitive definitions of terms and symbols A Head, K Lo, D Kang, R Fok, S Skjonsberg, DS Weld, MA Hearst Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 103 | 2021 |
| Genaug: Data augmentation for finetuning text generators SY Feng, V Gangal, D Kang, T Mitamura, E Hovy DeeLIO @EMNLP 2020, 2020 | 89 | 2020 |
| Benchmarking cognitive biases in large language models as evaluators R Koo, M Lee, V Raheja, JI Park, ZM Kim, D Kang Annual Meeting of the Association for Computational Linguistics (ACL) Findings, 2024 | 85 | 2024 |
| Read, revise, repeat: A system demonstration for human-in-the-loop iterative text revision W Du, ZM Kim, V Raheja, D Kumar, D Kang 🏆 In2Writing @ACL 2022, 2022 | 64 | 2022 |
| Understanding Iterative Revision from Human-Written Text W Du, V Raheja, D Kumar, ZM Kim, M Lopez, D Kang Annual Meeting of the Association for Computational Linguistics (ACL), 2022 | 60 | 2022 |
| Zero-shot natural language video localization J Nam, D Ahn, D Kang, SJ Ha, J Choi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 57 | 2021 |
| Earlier Isn't Always Better: Sub-aspect Analysis on Corpus and System Biases in Summarization T Jung, D Kang, L Mentch, E Hovy Empirical Methods in Natural Language Processing (EMNLP), 2019 | 55 | 2019 |
| CoEdIT: Text editing by task-specific instruction tuning V Raheja, D Kumar, R Koo, D Kang Empirical Methods in Natural Language Processing (EMNLP), 2023 | 41 | 2023 |
| A survey of diffusion models in natural language processing H Zou, ZM Kim, D Kang arXiv preprint arXiv:2305.14671, 2023 | 40* | 2023 |
| Style is NOT a single variable: Case Studies for Cross-Style Language Understanding D Kang, E Hovy Annual Meeting of the Association for Computational Linguistics (ACL), 2021 | 39* | 2021 |
| Detecting and Explaining Causes From Text For a Time Series Event D Kang, V Gangal, A Lu, Z Chen, E Hovy Empirical Methods in Natural Language Processing (EMNLP), 2017 | 39 | 2017 |
| Everyone’s voice matters: Quantifying annotation disagreement using demographic information R Wan, J Kim, D Kang Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14523 …, 2023 | 38 | 2023 |
| Does BERT Learn as Humans Perceive? Understanding Linguistic Styles through Lexica S Anugrah Hayati, D Kang, L Ungar EMNLP 2021, arXiv: 2109.02738, 2021 | 33* | 2021 |
| Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions D Kang, A Head, R Sidhu, K Lo, DS Weld, MA Hearst SDP @EMNLP 2021, 2020 | 32 | 2020 |
| Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents H Chae, Y Song, KT Ong, T Kwon, M Kim, Y Yu, D Lee, D Kang, J Yeo Empirical Methods in Natural Language Processing (EMNLP), 2023 | 30 | 2023 |
| Under the surface: Tracking the artifactuality of llm-generated data D Das, K De Langis, A Martin-Boyle, J Kim, M Lee, ZM Kim, SA Hayati, ... arXiv preprint arXiv:2401.14698, 2024 | 24* | 2024 |
Eduard HovyUniversity of Melbourne, CMUVerified email at andrew.cmu.edu
