Towards reducing hallucination in extracting information from financial reports using Large Language Models. - Bhaskarjit Sarmah; Dhagash Mehta; Stefano Pasquali; Tianjie Zhu (AIMLSystems, 2023)

Towards Enhanced Local Explainability of Random Forests: a Proximity-Based Approach. - Joshua Rosaler; Dhruv Desai; Bhaskarjit Sarmah; Dimitrios Vamvourellis; Deran Onay; Dhagash Mehta; Stefano Pasquali (CoRR, 2023)

Learning Embedded Representation of the Stock Correlation Matrix Using Graph Machine Learning. - Bhaskarjit Sarmah; Nayana Nair; Riya Jain; Dhagash Mehta; Stefano Pasquali (CIFEr, 2024)

Quantile Regression using Random Forest Proximities. - Mingshu Li; Bhaskarjit Sarmah; Dhruv Desai; Joshua Rosaler; Snigdha Bhagat; Philip Sommer; Dhagash Mehta (ICAIF, 2024)

Enhanced Local Explainability and Trust Scores with Random Forest Proximities. - Joshua Rosaler; Dhruv Desai; Bhaskarjit Sarmah; Dimitrios Vamvourellis; Deran Onay; Stefano Pasquali; Dhagash Mehta (ICAIF, 2024)

HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction. - Bhaskarjit Sarmah; Dhagash Mehta; Benika Hall; Rohan Rao; Sunil Patel; Stefano Pasquali (ICAIF, 2024)

How to Choose a Threshold for an Evaluation Metric for Large Language Models. - Bhaskarjit Sarmah; Mingshu Li; Jingrao Lyu; Sebastian Frank 004; Nathalia M. Castellanos; Stefano Pasquali; Dhagash Mehta (CoRR, 2024)

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation. - Bhaskarjit Sarmah; Kriti Dutta; Anna Grigoryan; Sachin Tiwari; Stefano Pasquali; Dhagash Mehta (CoRR, 2024)