39 citations · 67 across the 5 of their papers we have counts for
6 papers
When and Why does a Model Fail? A Human-in-the-loop Error Detection Framework for Sentiment Analysis
Zhe Liu, Yufan Guo, Jalal Mahmud
Although deep neural networks have been widely employed and proven effective in sentiment analysis tasks, it remains challenging for model developers to assess their models for err…
Accountable Error Characterization
Amita Misra, Zhe Liu, Jalal Mahmud
Customers of machine learning systems demand accountability from the companies employing these algorithms for various prediction tasks. Accountability requires understanding of sys…
Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation
Yash Bhalgat, Zhe Liu, Pritam Gundecha +2
Given that labeled data is expensive to obtain in real-world scenarios, many semi-supervised algorithms have explored the task of exploitation of unlabeled data. Traditional tri-tr…
Characterizing machine learning process: A maturity framework
Rama Akkiraju, Vibha Sinha, Anbang Xu +5
Academic literature on machine learning modeling fails to address how to make machine learning models work for enterprises. For example, existing machine learning processes cannot…
Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media
Tianran Hu, Anbang Xu, Zhe Liu +5
Chatbot has become an important solution to rapidly increasing customer care demands on social media in recent years. However, current work on chatbot for customer care ignores a k…
Fostering User Engagement: Rhetorical Devices for Applause Generation Learnt from TED Talks
Zhe Liu, Anbang Xu, Mengdi Zhang +2
One problem that every presenter faces when delivering a public discourse is how to hold the listeners' attentions or to keep them involved. Therefore, many studies in conversation…