Zhijing Jin
Cited by
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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
GraphIE: A Graph-Based Framework for Information Extraction
Y Qian, E Santus, Z Jin, J Guo, R Barzilay
arXiv preprint arXiv:1810.13083, 2018
Deep Learning for Text Style Transfer: A Survey
D Jin, Z Jin, R Mihalcea
arXiv preprint arXiv:2011.00416, 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
Hooks in the Headline: Learning to Generate Headlines with Controlled Styles
D Jin, Z Jin, JT Zhou, L Orii, P Szolovits, 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
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
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
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
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
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, B Schölkopf
arXiv preprint arXiv:2110.03618, 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
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
3d traffic simulation for autonomous vehicles in unity and python
Z Jin, T Swedish, R Raskar
arXiv preprint arXiv:1810.12552, 2018
Logical fallacy detection
Z Jin, A Lalwani, T Vaidhya, X Shen, Y Ding, Z Lyu, M Sachan, ...
arXiv preprint arXiv:2202.13758, 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
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
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