Zhijing Jin
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Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
D Jin*, Z Jin*, JT Zhou, P Szolovits
Proceedings of the AAAI conference on artificial intelligence 34 (05), 8018-8025, 2020
Deep learning for text style transfer: A survey
D Jin*, Z Jin*, Z Hu, O Vechtomova, R Mihalcea
Computational Linguistics 48 (1), 155-205, 2022
GraphIE: A graph-based framework for information extraction
Y Qian, E Santus, Z Jin, J Guo, R Barzilay
arXiv preprint arXiv:1810.13083, 2018
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
Hooks in the headline: Learning to generate headlines with controlled styles
D Jin, Z Jin, JT Zhou, L Orii, P Szolovits
arXiv preprint arXiv:2004.01980, 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
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
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
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
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
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
Proceedings of the 3rd International Workshop on Natural Language Generation …, 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
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, ...
arXiv preprint arXiv:2110.03618, 2021
Logical fallacy detection
Z Jin*, A Lalwani*, T Vaidhya, X Shen, Y Ding, Z Lyu, M Sachan, ...
arXiv preprint arXiv:2202.13758, 2022
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
State-of-the-art generalisation research in NLP: a taxonomy and review
D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ...
arXiv preprint arXiv:2210.03050, 2022
When to make exceptions: Exploring language models as accounts of human moral judgment
Z Jin*, S Levine*, F Gonzalez*, O Kamal, M Sap, M Sachan, R Mihalcea, ...
Advances in neural information processing systems 35, 28458-28473, 2022
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models
A Stolfo*, Z Jin*, K Shridhar, B Schölkopf, M Sachan
arXiv preprint arXiv:2210.12023, 2022
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
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
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