7 citations · 31 across the 12 of their papers we have counts for
13 papers · 1 filter
Generating Hierarchical Explanations on Text Classification Without Connecting Rules
Yiming Ju, Yuanzhe Zhang, Kang Liu +1
The opaqueness of deep NLP models has motivated the development of methods for interpreting how deep models predict. Recently, work has introduced hierarchical attribution, which p…
Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder
Fangyu Lei, Shizhu He, Xiang Li +2
In the real-world question answering scenarios, hybrid form combining both tabular and textual contents has attracted more and more attention, among which numerical reasoning probl…
ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains
Minjun Zhu, Yixuan Weng, Shizhu He +2
The ability of reasoning over evidence has received increasing attention in question answering (QA). Recently, natural language database (NLDB) conducts complex QA in knowledge bas…
Lifelong Intent Detection via Multi-Strategy Rebalancing
Qingbin Liu, Xiaoyan Yu, Shizhu He +2
Conventional Intent Detection (ID) models are usually trained offline, which relies on a fixed dataset and a predefined set of intent classes. However, in real-world applications,…
Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement
Xinyu Zuo, Pengfei Cao, Yubo Chen +4
Current models for event causality identification (ECI) mainly adopt a supervised framework, which heavily rely on labeled data for training. Unfortunately, the scale of current an…
LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification
Xinyu Zuo, Pengfei Cao, Yubo Chen +4
Modern models for event causality identification (ECI) are mainly based on supervised learning, which are prone to the data lacking problem. Unfortunately, the existing NLP-related…