Objective
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.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2023-DN-01
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
37129 Verona
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.