This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jiwan Chung, MIR Lab Yonsei University (https://jiwanchung.github.io/);
(2) Youngjae Yu, MIR Lab Yonsei University (https://jiwanchung.github.io/).
Table of Links
- Abstract and Intro
- Method
- Experiments
- Related Work
- Conclusion
- Limitations and References
- A. Experiment Details
- B. Prompt Samples
6. Limitations
Our study has some limitations, including:
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We experiment with only videos with English subtitles. However, our method can be extended to include multi-lingual contexts given a strong multilingual language model.
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The computation and memory requirement of our method is substantial due to its heavy reliance on the large language model, GPT-3.
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We evaluate Long Story Short with only a single instance of LLM (GPT-3).
Potential Risk. Summarizing the long video context with GPT-3 carries on ethical risks related to the open-ended nature of the language model. GPT-3 may (a) hallucinate fake facts about the content, (b) generate toxic utterances, or (c) implicitly embed social biases into the summary and the answer likelihoods.
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