* The key techinique behind the dataset collection is to enrich existing video datasets with aligned, cross-modality representations, which is achieved by leveraging off-the-shelf pre-trained models, e.g. captions to video frames and audio. The quality of the multi-modal datasets is directly affected by the selected models. However, this part is only briefly mentioned in Section 3.1. More ablations or discussions would be beneficial regarding this part, as I presume this affects the generic applicablity of the proposed dataset collection approach, i.e. whether the potential distribution shift between the pre-trained model checkpoint and the source video dataset would affect the quality of the generated dataset.
* The proposed model demonstrate impressive performance on many benchmarks (setting new SoTA scores) but more careful analysis probably is needed, especially for some pretty "old" benchmarks that the data might have been indirectly seen by the model via the "data curation" process. More details about the evaluation procedures would be helpful.
* There exists quite some grammatical errors and typos (e.g. L181-182, L212, L216, etc.) The paper would benefit from more careful revisions.
* The proposed model demonstrate impressive performance on many benchmarks (setting new SoTA scores) but more careful analysis probably is needed, especially for some pretty "old" benchmarks that the data might have been indirectly seen by the model via the "data curation" process. More details about the evaluation procedures would be helpful.