activity
20202024
most citedEvaluating the Correctness of Explainable AI Algorithms for Classification

18 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2024★ 2 cited

"My Grade is Wrong!": A Contestable AI Framework for Interactive Feedback in Evaluating Student Essays

Shengxin Hong, Chang Cai, Sixuan Du +3

Interactive feedback, where feedback flows in both directions between teacher and student, is more effective than traditional one-way feedback. However, it is often too time-consum…

econ.GN2021

An Investigation of the Impact of COVID-19 Non-Pharmaceutical Interventions and Economic Support Policies on Foreign Exchange Markets with Explainable AI Techniques

Siyuan Liu, Mehmet Orcun Yalcin, Hsuan Fu +1

Since the onset of the the COVID-19 pandemic, many countries across the world have implemented various non-pharmaceutical interventions (NPIs) to contain the spread of virus, as we…

cs.AI2021★ 18 cited

Evaluating the Correctness of Explainable AI Algorithms for Classification

Orcun Yalcin, Xiuyi Fan, Siyuan Liu

Explainable AI has attracted much research attention in recent years with feature attribution algorithms, which compute "feature importance" in predictions, becoming increasingly p…

cs.CY2020★ 5 cited

An Investigation of COVID-19 Spreading Factors with Explainable AI Techniques

Xiuyi Fan, Siyuan Liu, Jiarong Chen +1

Since COVID-19 was first identified in December 2019, various public health interventions have been implemented across the world. As different measures are implemented at different…

cs.AI2020★ 1 cited

Explainable AI for Classification using Probabilistic Logic Inference

Xiuyi Fan, Siyuan Liu, Thomas C. Henderson

The overarching goal of Explainable AI is to develop systems that not only exhibit intelligent behaviours, but also are able to explain their rationale and reveal insights. In expl…