Bipasha Banerjee

Evaluating and explaining LLM classification for automatic screening in Systematic Reviews

This research conducts a set of experiments using open-source Large Language Models with small parameters hosted on local servers to screen titles and abstracts against pre-defined eligibility criteria respective to each topic, and suggests that AI may indeed aid with initial relevance screening, but more research is n...

End-to-End Contextualized URL Extraction from Scholarly Papers

Evaluating and explaining LLM classification for automatic screening in Systematic Reviews

Evidence synthesis methods, such as systematic reviews (SR), require research teams to find, select, evaluate, and synthesize all available evidence to answer a specific research question in a reproducible and transparent, bias-reduced manner. Early in the process, teams must screen all unique titles and abstracts gath...

URL Extraction from Scholarly Documents: A Cross-Format Comparative Analysis

This study presents a systematic study evaluating URL extraction across six input formats and indicates that TEXTWAL achieves the best performance among single-format inputs, while TEXTWAL+LaTeX achieves the best overall URL extraction performance.