Summary of Non-halting Queries: Exploiting Fixed Points in Llms, by Ghaith Hammouri et al.
Non-Halting Queries: Exploiting Fixed Points in LLMs
by Ghaith Hammouri, Kemal Derya, Berk Sunar
First submitted to arxiv on: 8 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 proposed paper introduces a novel vulnerability in autoregressive models, specifically targeting fixed points that allow for the creation of non-halting queries. By exploiting these vulnerabilities, the researchers demonstrate the ability to craft queries that never terminate. The analysis reveals specific conditions under which this anomaly arises, including the presence of repeating token sequences beyond the context size at a temperature of zero. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new kind of bug has been found in some artificial intelligence models called autoregressive models. These models are used for language processing and can generate text based on what they’ve seen before. The problem is that certain queries, or questions, can be designed to never stop generating output. This means the model will keep producing text forever! To understand when this happens, the researchers looked at specific conditions, like when a pattern of repeating words appears beyond a certain point. |
Keywords
» Artificial intelligence » Autoregressive » Temperature » Token
