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of 9
pro vyhledávání: '"Santamaria, Selene Baez"'
We develop an artificial agent motivated to augment its knowledge base beyond its initial training. The agent actively participates in dialogues with other agents, strategically acquiring new information. The agent models its knowledge as an RDF know
Externí odkaz:
http://arxiv.org/abs/2406.19500
This paper discusses our approaches for task-oriented conversational modelling using subjective knowledge, with a particular emphasis on response generation. Our methodology was shaped by an extensive data analysis that evaluated key factors such as
Externí odkaz:
http://arxiv.org/abs/2308.01080
We present a new method based on episodic Knowledge Graphs (eKGs) for evaluating (multimodal) conversational agents in open domains. This graph is generated by interpreting raw signals during conversation and is able to capture the accumulation of kn
Externí odkaz:
http://arxiv.org/abs/2209.11746
This paper describes our contributions to the Shared Task of the 9th Workshop on Argument Mining (2022). Our approach uses Large Language Models for the task of Argument Quality Prediction. We perform prompt engineering using GPT-3, and also investig
Externí odkaz:
http://arxiv.org/abs/2209.08966
Autor:
Alivanistos, Dimitrios, Santamaría, Selene Báez, Cochez, Michael, Kalo, Jan-Christoph, van Krieken, Emile, Thanapalasingam, Thiviyan
Language Models (LMs) have proven to be useful in various downstream applications, such as summarisation, translation, question answering and text classification. LMs are becoming increasingly important tools in Artificial Intelligence, because of th
Externí odkaz:
http://arxiv.org/abs/2208.11057
The paper describes a flexible and modular platform to create multimodal interactive agents. The platform operates through an event-bus on which signals and interpretations are posted in a sequence in time. Different sensors and interpretation compon
Externí odkaz:
http://arxiv.org/abs/2206.00636
Autor:
Santamaria, Selene Baez, Manousogiannis, Emmanouil, Boomgaard, Guusje, Tran, Linh P., Szlavik, Zoltan, Sips, Robert-Jan
Background: Access to medical care is strongly dependent on resource allocation, such as the geographical distribution of medical facilities. Nevertheless, this data is usually restricted to country official documentation, not available to the public
Externí odkaz:
http://arxiv.org/abs/2204.05206
Autor:
Santamaría, Selene Báez, Baier, Thomas, Kim, Taewoon, Krause, Lea, Kruijt, Jaap, Vossen, Piek
We present EMISSOR: a platform to capture multimodal interactions as recordings of episodic experiences with explicit referential interpretations that also yield an episodic Knowledge Graph (eKG). The platform stores streams of multiple modalities as
Externí odkaz:
http://arxiv.org/abs/2105.08388
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