7 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 5 cited
Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity
Wrick Talukdar, Anjanava Biswas
As Large Language Models (LLMs) become increasingly sophisticated and ubiquitous in natural language processing (NLP) applications, ensuring their robustness, trustworthiness, and…
cs.CL2024★ 6 cited
Robustness of Structured Data Extraction from In-plane Rotated Documents using Multi-Modal Large Language Models (LLM)
Anjanava Biswas, Wrick Talukdar
Multi-modal large language models (LLMs) have shown remarkable performance in various natural language processing tasks, including data extraction from documents. However, the accu…
cs.CL2024★ 7 cited
Enhancing Clinical Documentation with Synthetic Data: Leveraging Generative Models for Improved Accuracy
Anjanava Biswas, Wrick Talukdar
Accurate and comprehensive clinical documentation is crucial for delivering high-quality healthcare, facilitating effective communication among providers, and ensuring compliance w…