Summary of Lighthouse: a Survey Of Agi Hallucination, by Feng Wang
LightHouse: A Survey of AGI Hallucination
by Feng Wang
First submitted to arxiv on: 8 Jan 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 tackles the challenge of hallucinations in artificial general intelligence (AGI) models. The authors provide an overview of the current state of research on AGI hallucinations, which is a critical bottleneck hindering AI development. They focus on large language models (LLMs) and multimodal AGI, highlighting the need for further research to overcome hallucination issues. The proposed directions for future research aim to advance our understanding of AGI hallucinations and ultimately push forward the development of strong AI. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine a super-smart computer that can understand and respond to any question or task. Sounds cool, right? But, there’s a problem – sometimes these computers make up things that aren’t true! This is called “hallucination” and it’s a major obstacle in the development of truly smart AI. The researchers are trying to figure out why this happens and how we can stop it from happening. They’re looking at big language models and other types of AI to see what’s going on. |
Keywords
* Artificial intelligence * Hallucination
