Effective Representation to Capture Collaboration Behaviors between Explainer and User
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Abstract (arXiv)
An explainable AI (XAI) model aims to provide transparency (in the form of justification, explanation, etc) for its predictions or actions made by it. Recently, there has been a lot of focus on building XAI models, especially to provide explanations for understanding and interpreting the predictions made by deep learning models. At UCLA, we propose a generic framework to interact with an XAI model in natural language.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jan 2022.
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Citing papers per year: 2022: 4.
4 papers.
- 2022Attention cannot be an Explanationcited by 4
- 2022Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Groundingcited by 3
- 2022Discourse Analysis for Evaluating Coherence in Video Paragraph Captionscited by 2
- 2022On the Importance of Karaka Framework in Multi-modal Groundingcited by 0
- 2022On the Importance of Karaka Framework in Multi-modal Grounding9 Apr 2022
- 2022Attention cannot be an Explanation26 Jan 2022
- 2022Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Grounding24 Jan 2022
- 2022Discourse Analysis for Evaluating Coherence in Video Paragraph Captions17 Jan 2022