Summary of Dyknow: Dynamically Verifying Time-sensitive Factual Knowledge in Llms, by Seyed Mahed Mousavi et al.
DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs
by Seyed Mahed Mousavi, Simone Alghisi, Giuseppe Riccardi
First submitted to arxiv on: 10 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 addresses a critical issue in Large Language Models (LLMs), which are trained on massive datasets collected at different timestamps. Current evaluations using static benchmarks do not account for time-sensitive changes to factual knowledge. To address this, the authors propose an approach to dynamically evaluate LLMs’ knowledge against Wikidata, a publicly available and up-to-date knowledge graph. The study evaluates twenty-four private and open-source LLMs, as well as four editing methods aimed at updating outdated facts. The results reveal that outdatedness is a widespread problem across state-of-the-art LLMs, with inconsistent answers generated when prompted with slight variations of question prompts. Furthermore, the performance of state-of-the-art knowledge editing algorithms is limited in reducing cases of outdatedness and output inconsistency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you have a super smart computer program that can answer questions about history or science. But what if this program’s answers are not accurate because it was trained on old information? This problem exists for many language models, which are like super smart AI assistants. To solve this issue, researchers developed a way to test these language models using a more up-to-date database of knowledge called Wikidata. They tested 24 different language models and found that most of them had outdated answers. They also tried different methods to update the outdated information, but they didn’t work very well either. |
Keywords
» Artificial intelligence » Knowledge graph
