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ARMADA

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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 bi... ver más

28/02/2029

UNIVR

Presupuesto desconocido

Líder del proyecto

UNIVERSITA DEGLI STUDI DI VERONA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto

HORIZON-MSCA-2023-DN-01-01: MSCA Doctoral Networks 2023 Expected Outcome:Project results are expected to contribute to the following outcomes:

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UNIVR

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Duración del proyecto: 47 meses Fecha Inicio: 2025-03-01
Fecha Fin: 2029-02-28

Líder del proyecto

UNIVERSITA DEGLI STUDI DI VERONA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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 domain knowledge, explainability and soundness of answers, reactivity via interactive correction workflows, and effectiveness and efficiency of computations. Due to the highly interdisciplinary aspect, the proposed program will ensure a number of training activities targeted to hone the skills of the trainees across different dimensions. The network provides research training with summer and winter schools on the multidisciplinary themes, as well as workshops and courses to foster complementary-skills, such as scientific writing, innovation, supervision, and management. This program importantly tackles the crucial EU needs for regulating AI by offering to train experts in the area of Conversational AI that will potentially advise EU bodies on technical matters related to the adoption of these technologies in critical disciplines, such as medicine, education, and business intelligence. The 8 organizations distributed in 7 countries and managed by a highly diverse team of expert researchers will form an interoperability scheme to share knowledge and skills.

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