Venue: ICLR 2023 TinyPapers

Reviews:

final_score: rating: High Potential (HP): a submission which meets the reviewing criteria and has potential to make an impact on the field
review_content: summary_of_contributions: This paper presents a novel architecture for a casual generative model-- an adaptation of  Canale et al.  with a directed acyclic graph (DAG) processing capability as an encoder input. The DAG captures casual relationships among feature variables.   
strengths_and_weaknesses: Strength 
1. The author's claims of a computationally efficient method are supported by empirical results. The findings show that the model requires fewer epochs to achieve the best result.
2. Findings are communicated clearly.

Weakness
1. The final distribution from the decoder is obtained by combining the intermediate representations of the encoder and the hidden states of the decoder. The authors did not mention the intuition of their design modification.
2. Reproducibility: The reader can reproduce the design. However, the authors did not share the code.





suggested_changes: Please provide the source code link.
review_title: null

final_score: rating: Needs Clarification (NC): a submission which does not meet the reviewing criteria and needs clarification for its described problem or solution
review_content: summary_of_contributions: This paper introduces an architecture for causal data generation based on the architecture Codecs, which is more computationally efficient.
strengths_and_weaknesses: 

Strengths:
1. Provide convincing empirical results to show the efficiency of the proposed approach. 

Weakness: 
1. The contribution and the novelty are not clear enough for this paper.  
2. The proposed approach incorporates the previous framework with slight modifications on encoder and decoder without illustrations on motivations, more analysis should be provided.


suggested_changes: 1. The writing of this paper should be improved, with more motivations and discussions for the proposed approach. 
2. The proposed approach is relatively incremental for current version.
review_title: null

Decision: Invite to archive