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pro vyhledávání: '"Pereira, Patricia A."'
Empathy and emotion prediction are key components in the development of effective and empathetic agents, amongst several other applications. The WASSA shared task on empathy and emotion prediction in interactions presents an opportunity to benchmark
Externí odkaz:
http://arxiv.org/abs/2407.03818
Autor:
Mendonça, John, Pereira, Patrícia, Menezes, Miguel, Cabarrão, Vera, Farinha, Ana C., Moniz, Helena, Carvalho, João Paulo, Lavie, Alon, Trancoso, Isabel
Task-oriented conversational datasets often lack topic variability and linguistic diversity. However, with the advent of Large Language Models (LLMs) pretrained on extensive, multilingual and diverse text data, these limitations seem overcome. Nevert
Externí odkaz:
http://arxiv.org/abs/2311.13910
Fuzzy Fingerprints have been successfully used as an interpretable text classification technique, but, like most other techniques, have been largely surpassed in performance by Large Pre-trained Language Models, such as BERT or RoBERTa. These models
Externí odkaz:
http://arxiv.org/abs/2309.04292
Autor:
Mendonça, John, Pereira, Patrícia, Moniz, Helena, Carvalho, João Paulo, Lavie, Alon, Trancoso, Isabel
Despite significant research effort in the development of automatic dialogue evaluation metrics, little thought is given to evaluating dialogues other than in English. At the same time, ensuring metrics are invariant to semantically similar responses
Externí odkaz:
http://arxiv.org/abs/2308.16797
Emotion Recognition in Conversations (ERC) has been gaining increasing importance as conversational agents become more and more common. Recognizing emotions is key for effective communication, being a crucial component in the development of effective
Externí odkaz:
http://arxiv.org/abs/2304.08216
Emotion Recognition in Conversations (ERC) is a key step towards successful human-machine interaction. While the field has seen tremendous advancement in the last few years, new applications and implementation scenarios present novel challenges and o
Externí odkaz:
http://arxiv.org/abs/2211.09172
In this paper, we propose an end-to-end sentiment-aware conversational agent based on two models: a reply sentiment prediction model, which leverages the context of the dialogue to predict an appropriate sentiment for the agent to express in its repl
Externí odkaz:
http://arxiv.org/abs/2207.11774
Autor:
Saraiva, Sofia, Pereira, Patrícia, Santos, Patrícia, Ramalho, Amílcar, Serra, Arménio C., Fonseca, Ana C.
Publikováno v:
In Reactive and Functional Polymers December 2024 205
Autor:
Pinto, Albano, Macário, Inês P.E., Marques, Sérgio M., Lourenço, Joana, Domingues, Inês, Botelho, Maria João, Asselman, Jana, Pereira, Patrícia, Pereira, Joana L.
Publikováno v:
In Science of the Total Environment 15 November 2024 951
Autor:
Sousa, Adelaide, Amaro, Andreia, Costa, Vera Marisa, Azevedo, Rui, Oliveira, Sara, Viana, Sofia, Reis, Flávio, Almeida, Agostinho, Matafome, Paulo, Dias-Pereira, Patrícia, Carvalho, Félix, Fernandes, Eduarda, Freitas, Marisa
Publikováno v:
In Food and Chemical Toxicology January 2025 195