Zhiwei Zhang


Abstract, Rationale, Stance: A Joint Model for Scientific Claim Verification
Zhiwei Zhang | Jiyi Li | Fumiyo Fukumoto | Yanming Ye
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Scientific claim verification can help the researchers to easily find the target scientific papers with the sentence evidence from a large corpus for the given claim. Some existing works propose pipeline models on the three tasks of abstract retrieval, rationale selection and stance prediction. Such works have the problems of error propagation among the modules in the pipeline and lack of sharing valuable information among modules. We thus propose an approach, named as ARSJoint, that jointly learns the modules for the three tasks with a machine reading comprehension framework by including claim information. In addition, we enhance the information exchanges and constraints among tasks by proposing a regularization term between the sentence attention scores of abstract retrieval and the estimated outputs of rational selection. The experimental results on the benchmark dataset SciFact show that our approach outperforms the existing works.


LDTM: A Latent Document Type Model for Cumulative Citation Recommendation
Jingang Wang | Dandan Song | Zhiwei Zhang | Lejian Liao | Luo Si | Chin-Yew Lin
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing