1. Have the author(s) thought about the reason why, information value is "stronger predictor" for dialogue(Complementarity in page 7 or discussion in page 8), is there any already existing linguistic theory which could explain it. If so, adding that will make this one a stronger paper.
2.It turns out to me that different information value serves as a strong predictor among the 5 chosen corpora, for example, in PROVO it is the syntactic information value. Again have the author(s) already had a potential hypothesis for this phenomenon?Is it practical to do a linguistic analysis on this 5 corpora to find the reason?
3. Is it possible that by increasing the set size of A_(x), the generated sentences sampled from "ancestral sampling" could have already covered some/all of the samples from other sampling methods, e.g., "temperature sampling"? As far as I know, both of the two mentioned sampling methods are based on the conditional probability, while typical sampling is a comparatively new sampling method which could cut off the dependence on the conditional probability to some degree and helps to generate more creative and diversify next sentences instead of entering receptive loop(Meister 2023).
Based on that,I would suggest the author(s) making a statistic report about the distributions of generated sentences from different sampling methods and maybe then making a selection of just two representative sampling methods based on the observation. Also a reference to temperature sampling is needed.
1. Have the author(s) thought about the reason why, information value is "stronger predictor" for dialogue(Complementarity in page 7 or discussion in page 8), is there any already existing linguistic theory which could explain it. If so, adding that will make this one a stronger paper.