Researchers at Cornell University Introduced HiQA: An Advanced Artificial Intelligence Framework for Multi-Document Question-Answering (MDQA)

February 26, 2024April 14, 2024 Rishabh Dwivedi

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Artificial Intelligence (AI) has revolutionized the way we interact with computers and process information. It has enabled machines to understand and respond to human language, leading to advancements in various applications such as chatbots, virtual assistants, and question-answering systems. Researchers at Cornell University have recently introduced HiQA, an advanced AI framework for Multi-Document Question-Answering (MDQA), which addresses the challenges posed by extensive collections of structurally similar documents.

The Challenge of Multi-Document Question-Answering

Traditional question-answering systems in Natural Language Processing (NLP) often struggle when faced with scenarios involving vast amounts of homogeneous data. In the case of multi-document QA (MDQA) tasks, where the system needs to integrate information from multiple documents to formulate coherent answers, the precision and relevance of responses can be compromised. This is where HiQA steps in to overcome these challenges and provide more accurate and relevant answers.