5 citations · 11 across the 10 of their papers we have counts for
10 papers · 1 filter
Human-Calibrated Automated Testing and Validation of Generative Language Models
Agus Sudjianto, Aijun Zhang, Srinivas Neppalli +2
This paper introduces a comprehensive framework for the evaluation and validation of generative language models (GLMs), with a focus on Retrieval-Augmented Generation (RAG) systems…
Downstream bias mitigation is all you need
Arkadeep Baksi, Rahul Singh, Tarun Joshi
The advent of transformer-based architectures and large language models (LLMs) have significantly advanced the performance of natural language processing (NLP) models. Since these…
Automatic Generation of Behavioral Test Cases For Natural Language Processing Using Clustering and Prompting
Ying Li, Rahul Singh, Tarun Joshi +1
Recent work in behavioral testing for natural language processing (NLP) models, such as Checklist, is inspired by related paradigms in software engineering testing. They allow eval…
Document Automation Architectures: Updated Survey in Light of Large Language Models
Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi +1
This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically…
Understanding Metrics for Paraphrasing
Omkar Patil, Rahul Singh, Tarun Joshi
Paraphrase generation is a difficult problem. This is not only because of the limitations in text generation capabilities but also due that to the lack of a proper definition of wh…
Document Automation Architectures and Technologies: A Survey
Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi +1
This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically…