Summary of Zkllm: Zero Knowledge Proofs For Large Language Models, by Haochen Sun and Jason Li and Hongyang Zhang
zkLLM: Zero Knowledge Proofs for Large Language Models
by Haochen Sun, Jason Li, Hongyang Zhang
First submitted to arxiv on: 24 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Cryptography and Security (cs.CR)
GrooveSquid.com Paper Summaries
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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 explores the implications of large language models (LLMs) on artificial intelligence and their potential legal challenges. Specifically, it examines how the treatment of LLMs’ parameters as intellectual property restricts direct research into these models. The authors discuss the impact of this trend on the legitimacy of LLMs and their applications across various domains. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about the big changes happening in artificial intelligence because of really smart computer programs called large language models. Some people are worried that these programs might not be as good or fair as we think they are, which could cause problems with how we use them. The researchers want to know why this is a problem and what we can do to make sure everything works out okay. |
