10 citations · 12 across the 6 of their papers we have counts for
6 papers
Fine-grainedly Synthesize Streaming Data Based On Large Language Models With Graph Structure Understanding For Data Sparsity
Xin Zhang, Linhai Zhang, Deyu Zhou +1
Due to the sparsity of user data, sentiment analysis on user reviews in e-commerce platforms often suffers from poor performance, especially when faced with extremely sparse user d…
Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment
Congzhi Zhang, Linhai Zhang, Deyu Zhou
Conventional multi-hop fact verification models are prone to rely on spurious correlations from the annotation artifacts, leading to an obvious performance decline on unbiased data…
Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspective
Qun Ma, Xiao Xue, Deyu Zhou +9
Computational experiments have emerged as a valuable method for studying complex systems, involving the algorithmization of counterfactuals. However, accurately representing real s…
EXPLAIN, EDIT, GENERATE: Rationale-Sensitive Counterfactual Data Augmentation for Multi-hop Fact Verification
Yingjie Zhu, Jiasheng Si, Yibo Zhao +3
Automatic multi-hop fact verification task has gained significant attention in recent years. Despite impressive results, these well-designed models perform poorly on out-of-domain…
Explainable Topic-Enhanced Argument Mining from Heterogeneous Sources
Jiasheng Si, Yingjie Zhu, Xingyu Shi +2
Given a controversial target such as ``nuclear energy'', argument mining aims to identify the argumentative text from heterogeneous sources. Current approaches focus on exploring b…
Consistent Multi-Granular Rationale Extraction for Explainable Multi-hop Fact Verification
Jiasheng Si, Yingjie Zhu, Deyu Zhou
The success of deep learning models on multi-hop fact verification has prompted researchers to understand the behavior behind their veracity. One possible way is erasure search: ob…