Summary of Trust & Safety Of Llms and Llms in Trust & Safety, by Doohee You et al.
Trust & Safety of LLMs and LLMs in Trust & Safety
by Doohee You, Dan Chon
First submitted to arxiv on: 3 Dec 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 The paper systematically reviews the current research landscape on trust and safety in Large Language Models (LLMs), with a focus on their novel application within the field of Trust and Safety itself. It investigates concerns about LLMs’ widespread adoption, including issues related to trust and safety in natural language processing tasks. The review provides a consolidated perspective on this emerging trend. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how Large Language Models (LLMs) are used to make sure online interactions are safe and trustworthy. It’s like a report card for LLMs, showing what they can do well and where they might need improvement. By understanding the strengths and weaknesses of these models, we can work on making them better tools for keeping the internet safe. |
Keywords
» Artificial intelligence » Natural language processing
