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20242026
most citedIntelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation

1k citations · 1.1k across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2026★ 18 cited

Guardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM)

Anjanava Biswas, Wrick Talukdar

The AI era has ushered in Large Language Models (LLM) to the technological forefront, which has been much of the talk in 2023, and is likely to remain as such for many years to com…

cs.CY2025

Gas Station of the Future: A Perspective on AI/ML and IoT in Retail Downstream

Wrick Talukdar

The gas station of the future is poised to transform from a simple fuel dispensing center into an intelligent retail hub, driven by advancements in Artificial Intelligence (AI), Ma…

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…

cs.CL2024★ 15 cited

Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling

Wrick Talukdar, Anjanava Biswas

While supervised learning models have shown remarkable performance in various natural language processing (NLP) tasks, their success heavily relies on the availability of large-sca…

cs.IR2024★ 1 cited

FinEmbedDiff: A Cost-Effective Approach of Classifying Financial Documents with Vector Sampling using Multi-modal Embedding Models

Anjanava Biswas, Wrick Talukdar

Accurate classification of multi-modal financial documents, containing text, tables, charts, and images, is crucial but challenging. Traditional text-based approaches often fail to…

cs.AI2024★ 1k cited

Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation

Anjanava Biswas, Wrick Talukdar

Comprehensive clinical documentation is crucial for effective healthcare delivery, yet it poses a significant burden on healthcare professionals, leading to burnout, increased medi…