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Multilingual and Cross-cultural interactions for context-aware, and bias-controlled dialogue systems for safety-critical applications

CORDIS · observation · Publication date unknown

lving humans-in-the-loop. Overall, ELOQUENCE’s project considers building on top and to improve of prior achievements in the domain of conversational agents, e.g. recently launched and public-domain Large Language Models (LLMs), such as chatGPT (e.g., more recent versions), or LaMDa most of them developed in non-EU countries. While including key industrial enterprises from Europe (i.e., Omilia, Telefonica, Synelixis), ELOQUENCE will validate the developed technology through (i) safety-critical scenarios with human-in-the-loop for security-critical applications (i.e., emergency services in call centres) and (ii) smart home assistants via information retrieval and fact-checking against an online knowledge base for lesser risky autonomous systems (i.e., home-assistants). ELOQUENCE will target the R&D of these novel conversational AI technologies in multilingual and multimodal environments and demonstrated in several pilots. Distributed and federated adaptation of Large Language Models, Multiliinguality, Multimodality, Human-in-the-loop, Bias-mitigation, Grounding

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recordType

award

status

SIGNED

region

EU

value

5072543.75

unit

EUR