).
Weaknesses - Some parts of the paper are difficult to follow, see also Typos etc below. - Ideally other baselines would also be included, such as the other works discussed in related work [29, 5, 6].
After the Authors' Response My weakness points after been addressed in the authors' response. Consequently I raised my score.
All unclear parts have been answered
The authors' explained why the chosen baseline makes the most sense. It would be great if this is added to the final version of the paper.
Questions - Do you think there is a way to test beforehand whether I(X_1, Y_1) would be lowered more than I(X_2, Y_1) beforehand? - Out of curiosity, did you consider first using Aug and then CF.CDA? Especially for the correlated palate result it could be interesting to see if now CF.CDA can improve. - Did both CDA and MMI have the same lambda_RL (Eq 9) value? From Figure 6 it seems the biggest difference between CDA and MMI is that MMI has more discontinuous phrase/tokens.
Typos, representation etc. - Line 69: Is X_2 defined as all features of X not in X_1? Stating this explicitly would be great. - Line 88: What ideas exactly do you take from [19] and how does your approach differ? - Eq 2: Does this mean Y is a value in [0, 1] for two possible labels? Can this be extended to more labels? This should be clarified. - 262: What are the possible Y values for TripAdvisor’s location aspect? - The definitions and usage of the various variables is sometimes difficult to follow. E.g. What exactly is the definition of X_2? (see also first point above). When does X_M become X_1? Sometimes the augmented data has a superscript, sometimes it does not. In line 131 the meaning of x_1 and x_2 are reverse, which can get confusing - maybe x’_1 and x’_2 would make it easier to follow together with a table that explains the meaning of different variables? - Section 2.3: Before line 116 mentioned the change when adding the counterfactual example, it would be helpful to first state what I(X_2, Y_1) and I(X_1, Y_1) are without it.
Minor points - Line 29: How is desired relationship between input text and target labels defined? - Line 44: What is meant by the initial rationale selector is perfect? It seems if it were perfect no additional work needs to be done. - Line 14, 47: A brief explanation of “multi-aspect” would be helpful - Figure 1: Subscripts s and t should be 1 and 2? - 184: Delete “the”
There is a broader impact section which discusses the limitations and dangers adequately.
- Line 44: What is meant by the initial rationale selector is perfect? It seems if it were perfect no additional work needs to be done.