gpt-score: 2.69
Papers with Code · CC BY-SA 4.0
Video-based Generative Performance Benchmarking (Detail Orientation))
The benchmark evaluates a generative Video Conversational Model with respect to Detail Orientation.
We curate a test set based on the ActivityNet-200 dataset, featuring videos with rich, dense descriptive captions and associated question-answer pairs from human annotations. We develop an evaluation pipeline using the GPT-3.5 model that assigns a relative score to the generated predictions on a scale of 1-5.
논문
gpt-score: 2.88
gpt-score: 2.91
gpt-score: 2.32
gpt-score: 3.02
gpt-score: 2.93
gpt-score: 3.20
gpt-score: 3.56
gpt-score: 2.96
gpt-score: 3.05
gpt-score: 3.03
gpt-score: 2.52
gpt-score: 2.18
gpt-score: 2.50
gpt-score: 3.18
gpt-score: 3.10