Venue: RBCDSAI DAI 2023 Conference

Reviews:

final_score: rating: 3: Accept 
review_content: summary: The authors present a representation learning framework for molecules based on functional groups.
strengths: > The problem is important and good algorithms can lead to significant impact.
> The proposed technique is tested on standard datasets and is shown to perform better against SOTA algorithms
weaknesses: The paper assumes the readers know a lot of domain specific terms/ algorithms. While this may be okay for a domain specific conference, it would be good to explain these  as if to a general audience. Specifically
-> What is SMILES?
-> What are the state of the art algorithms DMPNN and GEM and how is the proposed work different?
-> Any analysis on interpretability which is claimed as an important point would have been good to see.
review_title: null

final_score: rating: 4: Accept (candidate for best article)
review_content: summary: The authors present a functional group representation framework.
strengths: - The authors aim to address a problem that can make discovery of new medicines fasters and cheaper. 
- The preliminary evaluation is conducted using  the OCHEM database
weaknesses: - Some terms, such as SMILES,  need to be elaborated
- The objectives are specified, however elaborating the importance of addressing these objectives would make the article stronger. 
- The authors claim that 'the goodness is quantified using infidelity and sensitivity metrics', however they do not mention these metrics or give insights on why these metrics were chosen. 
- An explanation of the key insights from the results in Table 1 and Table 2 is missing.
review_title: null

Meta-review: Thank you for submitting your work to the Deployable AI conference, which is jointly organized by the Center for Responsible AI (CeRAI) & Robert Bosch Center for Deployable AI (RBC-DSAI), IIT Madras, Aalto University, University of Helsinki, University of Jyväskylä, and Oulu University.

We are pleased to inform you that your article is accepted. We invite you to give a short presentation on your work during the conference as a Spotlight talk. The talks are 15-minutes long and you can create slides to showcase the work. Please see the abstract reviews at the end of this email and consider the reviewer feedback when preparing your presentation. 

Your spotlight talk is scheduled on 07.06.2023 14.55 - 15.10 IST (12.25 – 12.40 EET)

All presenting authors must register for the conference – please do so ASAP if you haven’t already. For more information and registration, please visit the conference page: https://rbcdsai.iitm.ac.in/DAI-2023/index.html.

Please also ensure that all authors have their profiles on openreview. 
Decision: Accept (Oral Presentation)