- Lack of novelty: - Adversarial attacks by perturbing text has been done on many NLP models and image-text models. It is nicely summarized in related work of this paper. The only new effort is to take similar ideas and apply it on video-text models.
- Checklist (Ribeiro et. al., ACL 2020) had shown many ways to stress test NLP models and evaluate them. Video-text models could also be tested on some of those dimensions. For instance on changing NER.
- If you could propose any type of perturbation which is specific to video-text models (and probably not that important to image-text or just text models) will be interesting to see. Otherwise, this work, just looks like a using an already existing method on this new problem (video-text) which is just coming up.
- Is there a way to take any clue from the video to create harder negatives.
- Lack of novelty:- Adversarial attacks by perturbing text has been done on many NLP models and image-text models. It is nicely summarized in related work of this paper. The only new effort is to take similar ideas and apply it on video-text models.