Summary of A Comprehensive Survey Of Hallucination in Large Language, Image, Video and Audio Foundation Models, by Pranab Sahoo et al.
A Comprehensive Survey of Hallucination in Large Language, Image, Video and Audio Foundation Models
by Pranab Sahoo, Prabhash Meharia, Akash Ghosh, Sriparna Saha, Vinija Jain, Aman Chadha
First submitted to arxiv on: 15 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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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 rapid advancement of foundation models across language, image, audio, and video domains has shown remarkable capabilities in diverse tasks. However, the proliferation of FMs brings forth a critical challenge: the potential to generate hallucinated outputs, particularly in high-stakes applications. Recent developments aim to identify and mitigate the problem of hallucination in FMs, spanning text, image, video, and audio modalities. The paper synthesizes advancements in detecting and mitigating hallucination across various modalities, providing valuable insights for researchers, developers, and practitioners. It establishes a clear framework encompassing definition, taxonomy, and detection strategies for addressing hallucination in multimodal foundation models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Foundation models are incredibly advanced AI systems that can do many things. But sometimes they make mistakes by creating fake information. This is a big problem because it could happen in important situations. A new paper looks at how to find and fix these mistakes, or “hallucinations,” in different types of foundation models. The paper shows what researchers have been doing to solve this problem and provides a guide for others to follow. |
Keywords
» Artificial intelligence » Hallucination
