Note that a similar idea had already been suggested by Shen et al. (2025) in Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism (https://arxiv.org/abs/2506.01979), but with lower performance.
I'm not sure what you'd call a "pioneering scientific advancement", but there is an increasing amount of examples showing that LLMs can be used for research (with agents, particularly). A survey about this was published a few months ago: https://aclanthology.org/2025.emnlp-main.895.pdf
What we also learned after GPT-3.5 is that, to circumvent the need for new training data, we could simply resort to existing LLMs to generate new, synthetic data. I would not be surprised if the em dash is the product of synthetically generated data (perhaps forced to be present in this data) used for the training of newer models.
To add on what's been said already on slide decks, another great slide creation package in Typst is touying[1]. I've used it to create my own academic theme[2] for courses or conference presentations.
For *ACL you'd have to justify your wish to change reviewers, though; and you need a good reason for that. I don't know how much reviewers changes for a resubmission are solely due to reviewers' unavailability but it seems unlikely all three of them got removed from the reviewer pool.