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Reliable Conversational Domain-specific Data Exploration and Analysis

CORDIS · observation · Publication date unknown

Reliable Conversational Domain-specific Data Exploration and Analysis Conversational AI and Large Language Models (LLMs) such as ChatGPT and Bard promise to answers complex problems by performing simple conversations. Unfortunately, their answering processes are inscrutable, as well as prone to bias, hallucinations, and high computational costs. The ARMADA doctoral network will train 15 highly skilled Early Stage Researchers to specialize in the area of Conversational AI and the challenges associated to the recent advances in developing LLMs, when assisting analysis in sensitive domains. These specialists will acquire unique knowledge and skills in Natural Language Processing, Machine Learning, Data Management, and Algorithms to evaluate and improve the reliability of LLMs. A reliable LLM will produce timely, consistent, and verifiable answers, and provide guidance to the user in important decision-making processes. This will build across 5 important axes: alignment with dom

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recordType

award

status

SIGNED

region

EU

value

3289140

unit

EUR