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Author

Shashank Parmar

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Aug 2026

RAG-test: a framework to evaluate RAG chatbot performance and measure productivity gains

This paper proposes RAG-Test, a developer-centric and unified framework that automates test case generation, attribution validation, and productivity estimation and introduces a theoretical productivity gains model, estimating chatbot efficiency improvements over search engines.

Shashank Parmar · 0 citations
Conference Jul 2026

Statistical Edge Graphs for Tabular Learning with Graph Neural Networks

Tabular data are central to many real-world applications, yet deep learning models often underperform compared to tree-based methods due to limited relational inductive bias. We propose a unified framework that models each tabular instance as an instance-level statistical feature graph to enable learning with Graph Neu...

Shashank Parmar · 0 citations

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