Multimodality, a Hit or Miss! Exploring the potency of LLM in Multimodal Review Analysis for Prominent E-commerce Brands
Authors: Sarmistha Das, Anurag Deo, Toshit Tejasvat, Sriparna Saha


Reviewer paper summaries: This paper first introduces a review corpus in which each review is annotated along with aspects. Then, using the corpus, it presents results from various models for aspect and complaint identification and summarization.
Summary of strengths: * The paper is well-motivated.  Aspect-based review mining can be useful for improving products, services, and user experience.  

* The review corpus introduced can be potentially useful for future research.
Summary of weaknesses: * The main issue is the exposition. The writing looks rushed and lacks focus and structure, making it difficult to recognize the significance of the contributions. Subheads are all over the place, and the informal style doesn't work because of the suboptimal paper organization and cohesion. 

Minor - 
* It is unclear how images are used. Do annotations map review text to objects or segments in the images accompanying the reviews?
Comments, suggestions and typos: * Consider structuring the paper for clarity and focus and contextualizing it better within existing work. I recommend focusing on the new corpus and clearly describing the details and the methodology used in curating it. 

* At a minimum, cite existing review corpora such as Yelp, Amazon,  TripAdvisor, etc.
Overall assessment scores: 1.5