| Is BERT Really Robust? A Strong Baseline for Natural Language Attackon Text Classification and Entailment D Jin, Z Jin, JT Zhou, P Szolovits arXiv preprint arXiv:1907.11932, 2019 | 481 | 2019 |
| GraphIE: A Graph-Based Framework for Information Extraction Y Qian, E Santus, Z Jin, J Guo, R Barzilay arXiv preprint arXiv:1810.13083, 2018 | 73 | 2018 |
| Deep Learning for Text Style Transfer: A Survey D Jin, Z Jin, R Mihalcea arXiv preprint arXiv:2011.00416, 2020 | 44 | 2020 |
| IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation Z Jin, D Jin, J Mueller, N Matthews, E Santus arXiv preprint arXiv:1901.11333, 2019 | 43* | 2019 |
| Hooks in the Headline: Learning to Generate Headlines with Controlled Styles D Jin, Z Jin, JT Zhou, L Orii, P Szolovits http://zhijing-jin.com/files/papers/Hooks_in_the_Headline_2019.pdf, 2019 | 21 | 2019 |
| GenWiki: A dataset of 1.3 million content-sharing text and graphs for unsupervised graph-to-text generation Z Jin, Q Guo, X Qiu, Z Zhang Proceedings of the 28th International Conference on Computational …, 2020 | 18 | 2020 |
| Tasty burgers, soggy fries: Probing aspect robustness in aspect-based sentiment analysis X Xing, Z Jin, D Jin, B Wang, Q Zhang, X Huang arXiv preprint arXiv:2009.07964, 2020 | 16 | 2020 |
| Cyclegt: Unsupervised graph-to-text and text-to-graph generation via cycle training Q Guo, Z Jin, X Qiu, W Zhang, D Wipf, Z Zhang arXiv preprint arXiv:2006.04702, 2020 | 15 | 2020 |
| Deep natural language processing to identify symptom documentation in clinical notes for patients with heart failure undergoing cardiac resynchronization therapy RE Leiter, E Santus, Z Jin, KC Lee, M Yusufov, I Chien, A Ramaswamy, ... Journal of Pain and Symptom Management 60 (5), 948-958. e3, 2020 | 13 | 2020 |
| A simple baseline to semi-supervised domain adaptation for machine translation D Jin, Z Jin, JT Zhou, P Szolovits arXiv preprint arXiv:2001.08140, 2020 | 10* | 2020 |
| P2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation Q Guo, Z Jin, N Dai, X Qiu, X Xue, D Wipf, Z Zhang | 9* | |
| Relation of the relations: A new paradigm of the relation extraction problem Z Jin, Y Yang, X Qiu, Z Zhang arXiv preprint arXiv:2006.03719, 2020 | 8 | 2020 |
| How good is NLP? a sober look at NLP tasks through the lens of social impact Z Jin, G Chauhan, B Tse, M Sachan, R Mihalcea arXiv preprint arXiv:2106.02359, 2021 | 6 | 2021 |
| Causal direction of data collection matters: Implications of causal and anticausal learning for NLP Z Jin, J von Kügelgen, J Ni, T Vaidhya, A Kaushal, M Sachan, B Schölkopf arXiv preprint arXiv:2110.03618, 2021 | 5 | 2021 |
| Fork or fail: Cycle-consistent training with many-to-one mappings Q Guo, Z Jin, Z Wang, X Qiu, W Zhang, J Zhu, Z Zhang, W David International Conference on Artificial Intelligence and Statistics, 1828-1836, 2021 | 5 | 2021 |
| Mining the cause of political decision-making from social media: A case study of COVID-19 policies across the US states Z Jin, Z Peng, T Vaidhya, B Schoelkopf, R Mihalcea Findings of the Association for Computational Linguistics: EMNLP 2021, 288-301, 2021 | 2 | 2021 |
| 3d traffic simulation for autonomous vehicles in unity and python Z Jin, T Swedish, R Raskar arXiv preprint arXiv:1810.12552, 2018 | 2 | 2018 |
| Logical fallacy detection Z Jin, A Lalwani, T Vaidhya, X Shen, Y Ding, Z Lyu, M Sachan, ... arXiv preprint arXiv:2202.13758, 2022 | 1 | 2022 |
| Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning H Wang, Z Jin, J Cao, GPC Fung, KF Wong arXiv preprint arXiv:2110.08254, 2021 | 1 | 2021 |
| An artificial intelligence algorithm to identify documented symptoms in patients with heart failure who received cardiac resynchronization therapy (s717) R Leiter, E Santus, Z Jin, K Lee, M Yusufov, E Moseley, Y Qian, J Guo, ... Journal of Pain and Symptom Management 59 (2), 537-538, 2020 | 1 | 2020 |
Di JinApplied Scientist of Amazon Alexa AIVerified email at mit.edu
