Summary of Explaining Arguments’ Strength: Unveiling the Role Of Attacks and Supports (technical Report), by Xiang Yin et al.
Explaining Arguments’ Strength: Unveiling the Role of Attacks and Supports (Technical Report)
by Xiang Yin, Potyka Nico, Francesca Toni
First submitted to arxiv on: 22 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes Relation Attribution Explanations (RAEs) as a novel approach to quantify the strength of arguments under gradual semantics. By adapting Shapley values from game theory, RAEs provide fine-grained insights into the role of attacks and supports in bipolar argumentation. The authors demonstrate that RAEs satisfy several desirable properties and propose a probabilistic algorithm for efficient approximation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand how to measure the strength of arguments by considering both the supporting and attacking points. It proposes a new way called Relation Attribution Explanations (RAEs) which takes into account these important factors. The authors show that this approach works well in real-life applications like detecting fraud and understanding language models. |
Keywords
* Artificial intelligence * Semantics
