Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Human-Centered AI"”.
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Natural Language Processing per Human-centered AI
Nonostante i recenti progressi che hanno permesso ai sistemi di Intelligenza Artificiale (AI) di raggiungere prestazioni comparabili a quelle umane su benchmark consolidati, le tecnologie allo stato dell’arte mostrano ancora un calo di performance quando vengono applicate a compiti altamente …
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Intelligent dialog agent modeling in human-centered artificial intelligence applications
… Dialog systems have been integral in which ways humans and AI models can interact across multiple domains such as healthcare, customer service, and education. With the recent advancements in deep learning and pre-trained language models (PLMs), dialog systems have shown impressive performance in …
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From Dialogue to Decision: An LLM-Powered Framework for Analyzing Collective Idea Evolution and Voting Dynamics in Deliberative Assemblies
… advance, how perspectives evolve, and why certain recommendations succeed remain opaque and underexamined. This thesis addresses these gaps by investigating: (1) How might we trace the evolution and distillation of ideas into concrete recommendations within deliberative assemblies? and (2) How …
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Socially-Aware Machine Learning: Towards Leveraging the Relationship between Narrative Comprehension and Mentalizing
… by which people organize, understand, and explain the social world. Research suggests that exposure to narratives improves mentalizing, referring to the capacity to forecast and reason about others' mental states. Simultaneously, enhanced mentalizing abilities are closely linked to exhibiting …
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Toward AI-Mediated Immersive Sensemaking with Gaze-Aware Semantic Interaction
… an analyst's interest from their gaze so that an AI assistant guides foraging and supports synthesis while preserving analysts' agency over the layout? Specifically, we need methods that (a) predict perceived relevance at document and term levels during multi-document investigations, and (b) …