A few weeks ago, we launched ScarfBench, a benchmark for evaluating AI-assisted application modernization.
🌐 https://t.co/SNLJBWdHB0
📖 Insights: https://t.co/GTkFPmeSRW
If you find it useful:
⬆️ Upvote the blog: https://t.co/GTkFPmeSRW
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Check out ScarfBench, Self-Contained Application Refactoring benchmark, an open benchmark suite and public leaderboard designed to evaluate agentic enterprise Java migrations across Jakarta, Quarkus and Spring frameworks.
https://t.co/M9foj97J5m
R1- Accept
R2-Borderline Accept
R3-Borderline Reject
R4-Borderline Reject
Meta Review - Reject. There was limited discussion between the reviewers, but no strong champion of the paper came out.
If only we can see the positive side of things..
#AAAI2022#BePositive
If you are attending AAAI'21. I welcome you to listen to the presentation "Graph Neural Network to Dilute Outliers for Refactoring Monolith Application" from @utk_is_here from 10PM-12AM IST and on Friday 2-4 PM
https://t.co/OH3Kes2LwU
https://t.co/4TOJHor0tH
#AAAI21#ibmresearch
I am looking for research papers where a *deep learning model* is explained in a table. Ex: https://t.co/2T9aKklrtG (Table 1,2). If you come across research papers with tables explaining a DL model design, it would be great if you could share the paper (or the link) with me!