Summary of Development Of An Ai Anti-bullying System Using Large Language Model Key Topic Detection, by Matthew Tassava et al.
Development of an AI Anti-Bullying System Using Large Language Model Key Topic Detection
by Matthew Tassava, Cameron Kolodjski, Jordan Milbrath, Adorah Bishop, Nathan Flanders, Robbie Fetsch, Danielle Hanson, Jeremy Straub
First submitted to arxiv on: 19 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 AI anti-bullying system identifies coordinated attacks on social media, characterizes them, and proposes remedies. A large language model (LLM) populates an expert system-based network model to facilitate analysis and response activities, such as generating report messages for social media companies. The paper presents the system and evaluates the LLM’s effectiveness in populating the model. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This AI anti-bullying system helps stop online bullying by identifying attacks and suggesting ways to fix them. It uses a special computer program (LLM) to make a detailed map of how bullying happens, so it can be stopped. This system is important because it can help keep people safe from mean behavior on social media. |
Keywords
» Artificial intelligence » Large language model
