Hallucination Pair-wise Detection (1-ref)
3 papers with code • 1 benchmarks • 0 datasets
Most implemented papers
CLIPScore: A Reference-free Evaluation Metric for Image Captioning
jmhessel/clipscore
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EMNLP 2021
Image captioning has conventionally relied on reference-based automatic evaluations, where machine captions are compared against captions written by humans.
Mutual Information Divergence: A Unified Metric for Multimodal Generative Models
Based on a recent trend that multimodal generative evaluations exploit a vison-and-language pre-trained model, we propose the negative Gaussian cross-mutual information using the CLIP features as a unified metric, coined by Mutual Information Divergence (MID).
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
Large language models (large LMs) are susceptible to producing text that contains hallucinated content.
