The original training/validation data and trained baselines are available online (details on its construction are available in the paper that constructed this dataset).
This topic serves to collect additional resources that might be helpful for participants (during the shared task but also post-hoc), be it complementary training/evaluation data, code, or trained models.
Please feel free to share your resources here if you think they might be helpful to others.
There is a very cool project of @janetzhong82, Beicheng, and Ollie on clickbait spoiling that used abstractive question answering (here is the thread on Twitter). Their repository (including a supplementary dataset that might be useful for training/validation and code) is available on GitHub.
Markus Sverdvik Heiervang wrote a master thesis on clickbait spoiling that is available online.
The thesis looks very cool, and he also did go the extra mile and published trained models on Hugging Face that might be very helpful in this shared task.
This paper (accepted at EMNP 2022) might has some pre-training approaches that might be helpful for spoiling as well [2205.10455] Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection