129 lines
14 KiB
Markdown
129 lines
14 KiB
Markdown
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- venue:: [[MODELS]]
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year:: 2023
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- FT CFP - [MODELS 2023 - Foundation Track - MODELS 2023 (researchr.org)](https://conf.researchr.org/track/models-2023/models-2023-technical-track#Foundations-Track)
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- PT CFP - [MODELS 2023 - PracticeTrack - MODELS 2023 (researchr.org)](https://conf.researchr.org/track/models-2023/models-2023-technical-track#Practice-Track)
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- {:height 521, :width 980}
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- # Managed paper
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- {{query (and (property :status) (namespace [[editoringchairing]]))(property :status)}}
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query-table:: true
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query-properties:: [:block :decision]
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query-sort-by:: decision
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query-sort-desc:: true
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- [[#green]]==**(34) Automated Domain Modeling with Large Language Models: A Comparative Study**==
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external-link:: [Reviews and Comments on Submission 34 (easychair.org)](https://easychair.org/conferences/submission_reviews?submission=6475366;a=30415336#{fr:Ahy2ihv81nQ0})
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file:: _1685349649376_0.pdf)
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status:: [[METAREVIEW_READY]]
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decision:: [[ACCEPTED]]
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- Metareview
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- The paper explores the application of Large Language Models (LLMs) for the automatic creation of domain models, specifically comparing two LLMs: GPT3.5 and GPT4. Although the paper addresses an interesting and relevant problem and is well-written and well-structured, the reviewers have raised a few concerns:
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- *Distinctive Characteristics of Experiments*: It is important to highlight the unique aspects of the conducted experiments that differentiate the validation of the generated domain models from generic text. In other words, what specific elements or techniques were employed to ensure the validity and relevance of the generated domain models?
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- *Contribution and Implications*: Further elaboration is needed regarding the contribution of this work and its implications for the modeling community. How does this research advance the current state of the field, and what potential impact does it have on future modeling approaches or applications?
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- *Clarification on Chain-of-Thought*: It would be helpful to provide an explanation of how Chain-of-Thought is used within the framework of the experiments and its significance in the context of domain model creation. Can you please provide clarification on the utilization of Chain-of-thought in the context of the paper?
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- *Performance Comparison with Baseline*: A comparison with a baseline, such as Random Search, is mentioned. The reviewers are interested in understanding how the Language Models (LLMs) perform in comparison to this baseline. Specifically, there is a mention of some precision and recall values falling below 50%. It would be beneficial to provide a detailed analysis of the performance metrics and highlight any significant differences between the LLMs and the baseline.
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- *Differences Among Models*: Considering that the dataset consists of 10 models with approximately the same number of elements, how do these models differ from each other?
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- The paper investigates the adoption of Large Language Models to automatically create domain models. Two LLMs, namely GPT3.5 and GPT4, have been used and copared. The paper is about a very interesting and relevant problem. It is well written and structured. However, there are the following concerns from the reviewers:
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- What are the distinctive characteristics of the conducted experiments that differentiate the validation of the generated domain models from generic text?
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- Could you provide further elaboration on the contribution of this work and its implications for the modeling community?
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- Can you please provide clarification on the utilization of Chain-of-thought in the context of the paper?
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- In comparison to a baseline such as Random Search, how do the Language Models (LLMs) perform? Particularly, as some precision and recall values fall below 50%.
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- Considering that the dataset consists of 10 models with approximately the same number of elements, how do these models differ from each other?
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- [[#red]]==**(41) A metamodel for the representation of solar plant implantation contexts and collective self-consumption loops creation.**==
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external-link:: [Reviews and Comments on Submission 41 (easychair.org)](https://easychair.org/conferences/submission_reviews?a=30415336;submission=6475808)
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file:: 
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status:: [[METAREVIEW_READY]]
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decision:: [[REJECTED]]
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- Dear authors,
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Thank you for your response to the questions raised in the previous metareview. However, I must convey that the reviewers remain unsatisfied with the provided response. The primary concern that remains unanswered is the limited discussion on the lessons learned from the proposed application. Additionally, the paper lacks sufficient details explaining how constraints are specified and when they are checked during the process. The innovative aspects of the paper in the context of applied modeling research also appear unclear.
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Considering these arguments, the final decision has been made to reject the paper. However, we believe that the paper can be improved and submitted to another venue by addressing the following changes:
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- Provide a more comprehensive explanation of the role of the metamodeling phase as presented in the paper.
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- Emphasize the novelty of the proposed approach from a modeling perspective.
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- Clarify the different phases of the process involving the definition and assessment of model constraints.
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- We believe that incorporating these modifications can significantly enhance the quality and relevance of the paper.
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- "--- MR1 Metareview ---"
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- The paper has been classified as a Practice track contribution due to a violation of the double-blind rules. While the paper explores the application of modeling concepts to an interesting problem, the following questions have been raised:
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- What are the unique challenges in the specific application scenario that render it impractical to adapt previous work? It is essential to clearly identify and explain the distinct challenges that necessitate a new approach, highlighting why existing solutions cannot be readily applied.
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- How does the proposed approach enhance the state of practice in modeling and analysis?
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- What was the efficacy of employing metamodeling for the considered problem? Were any valuable lessons or insights gained from this approach?
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- Why was UML not utilized during the instantiation phase, and why were knowledge graphs chosen instead? It would be beneficial to explain the reasoning behind this decision and how it relates to the specific requirements and characteristics of the problem domain.
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- Did you consider using OCL (Object Constraint Language) to express static constraints over the domain? If so, what were the reasons for not choosing to use it? Providing an explanation for the choice of constraints expression language will help clarify the decision-making process.
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- [[#red]]==**(23) Model-Driven Verification of Data Science Pipelines Execution**==
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external-links:: [Reviews and Comments on Submission 23 (easychair.org)](https://easychair.org/conferences/submission_reviews?a=30415336;submission=6473914#{fr:385KGhb7x5ST})
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file:: 
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status:: [[METAREVIEW_READY]]
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decision:: [[EARLY_REJECT]]
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collapsed:: true
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- Dear authors,
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- The reviewers acknowledge the significance of techniques and tools that enhance the quality and reproducibility of data science processing. However, they have identified substantial concerns regarding the maturity of the proposed approach, which limit its suitability as both a Foundation Track and Practice Track paper.
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- Therefore, based on the current form of the paper, we regret to inform you that it cannot be accepted. We hope that you will find the reviewers' feedback valuable in refining your work for potential publication in a future venue.
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- Best regards,
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- [[#red]]==**(72) MSArch: A Graphical Modeling Language for MicroService Architecture Design**==
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external-link:: [Reviews and Comments on Submission 72 (easychair.org)](https://easychair.org/conferences/submission_reviews?a=30415336;submission=6476675#{fr:rsIl8svwBnxT})
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file:: 
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decision:: [[EARLY_REJECT]]
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status:: [[METAREVIEW_READY]]
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collapsed:: true
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- The paper presents a graphical modeling language designed for describing systems based on MicroServices. However, the reviewers share a unanimous perspective regarding the lack of novelty, strengths, and limitations of the proposed approach. Consequently, due to these concerns raised by the reviewers, the paper cannot be accepted in its current form.
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- Nevertheless, the reviewers have provided specific suggestions that we believe will be valuable in enhancing the paper for potential publication in a future venue. We hope you will find these suggestions useful as you work towards improving the quality of the research.
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- [[#red]]==**(49) Systems Architecture Meta-Model for the MBSE Grid Framework**==
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external-link:: [Reviews and Comments on Submission 49 (easychair.org)](https://easychair.org/conferences/submission_reviews?a=30415336;submission=6476007#{fr:3PPpjPTiUqyG})
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file:: 
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decision:: [[EARLY_REJECT]]
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status:: [[METAREVIEW_READY]]
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collapsed:: true
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- The paper utilizes the MBSE Grid Framework to establish connections between terminology and concepts outlined in the System Engineering Handbook and their counterparts in SysML. Various metamodels have been proposed to facilitate the creation of a shared vocabulary for systems engineers. Regrettably, all the reviewers have identified multiple concerns regarding the presentation, novelty, and practicality of the proposed metamodels. Consequently, the paper cannot be accepted in the current form.
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- Nevertheless, the reviewers have provided specific suggestions that we believe will be valuable in enhancing the paper for potential publication in a future venue. We hope you will find these suggestions useful in your efforts to improve the work.
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- [[#red]]==**(85) From Natural Language to DSLs: Using Large Language Models for Model-Driven Software Engineering**==
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external-link:: [Reviews and Comments on Submission 85 (easychair.org)](https://easychair.org/conferences/comment_added?a=30415336;submission=6476993;watch=1#{fr:cGKhk9I0j8R8})
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file:: 
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decision:: [[EARLY_REJECT]]
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status:: [[METAREVIEW_READY]]
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collapsed:: true
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- The paper addresses an interesting and significant topic. However, the reviewers express concerns regarding the presentation of the proposed approach. They note that while ChatGPT is utilized to generate domain-specific languages, the methodology employed is not adequately explained, resulting in a lack of clarity regarding the research contributions.
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- Nevertheless, the reviewers have provided specific suggestions that we believe will be valuable in improving the paper for potential publication in the future. We hope you find these suggestions helpful as you work towards enhancing the quality of the research.
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- [[#red]]==**(113) Conceptualizing Digital Twins for Decision Making: Is my Digital Twin Behaving?**==
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external-link:: https://easychair.org/conferences/submission_reviews?a=30415336;submission=6477335
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file:: 
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decision:: [[EARLY_REJECT]]
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status:: [[METAREVIEW_READY]]
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collapsed:: true
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- The paper introduces a reference architecture for facilitating the design of digital twins and presents a technique for quantifying the fidelity of digital twins using logistic regression. While the paper presents interesting ideas, it is affected by several issues regarding the practical benefits of the proposed approach. The absence of evaluation and comparison with existing baselines renders the paper unsuitable for publication in its current form.
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- However, the reviewers have provided specific suggestions to improve the paper, and we believe these recommendations will be valuable in preparing a new submission.
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- [[#red]]==**(143) Towards SysML v2 as a Variability Modeling Language**==
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external-links:: https://easychair.org/conferences/submission_reviews?submission=6484068;a=30415336
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file:: 
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decision:: [[EARLY_REJECT]]
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status:: [[METAREVIEW_READY]]
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collapsed:: true
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- The reviewers recognize the importance of the problem addressed in the paper. However, they all express concerns regarding the proposed approach. They find the paper not convincing due to the absence of a comprehensive comparison with relevant related work. Additionally, it has been deemed unsuitable for the "New Ideas and Vision Papers" category, as it is considered a technical paper offering incremental contributions to an existing body of research.
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- Reviewers have provided specific suggestions to improve the paper, and we believe these recommendations will be valuable in preparing a new submission.
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- # Guidelines
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- # TIMELINEs
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- First round discussion to be done by [[04-06-2023]]
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- ((647454d7-9d84-4677-b36f-fd6083044eef))
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- ((647454e3-9207-4d66-b4d5-954960053292))
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- ((647454ef-7508-4be2-ac97-d0c6c2e723ae))
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- ((64745518-3912-4834-8015-5dbafc26f072))
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- Early accept recommendations
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- # TODOs
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- DONE Manage [[issue]] about Paper-23 and Paper-41 - [http://s.diruscio.org/F9rGV](http://s.diruscio.org/F9rGV)
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date-submitted:: [[02-05-2023]]
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- DONE [[MODELS 2023 - First round of discussion]]
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- [[25-05-2023]] 20:37 [MODELS 2023 - First round of discussion - davide.diruscio@gmail.com - Gmail](https://mail.google.com/mail/u/0/#search/model/FMfcgzGsmhcKtDtkmzjMBXpQxqLrcjWT) |