Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Welch, Charles"'
Autor:
Nie, Shangrui, Fromm, Michael, Welch, Charles, Görge, Rebekka, Karimi, Akbar, Plepi, Joan, Mowmita, Nazia Afsan, Flores-Herr, Nicolas, Ali, Mehdi, Flek, Lucie
While preliminary findings indicate that multilingual LLMs exhibit reduced bias compared to monolingual ones, a comprehensive understanding of the effect of multilingual training on bias mitigation, is lacking. This study addresses this gap by system
Externí odkaz:
http://arxiv.org/abs/2407.05740
Autor:
Sotolar, Ondrej, Formanek, Vojtech, Debnath, Alok, Lahnala, Allison, Welch, Charles, FLek, Lucie
Empathetic response generation is a desirable aspect of conversational agents, crucial for facilitating engaging and emotionally intelligent multi-turn conversations between humans and machines. Leveraging large language models for this task has show
Externí odkaz:
http://arxiv.org/abs/2406.19071
Autor:
Sarumi, Olufunke O., Neuendorf, Béla, Plepi, Joan, Flek, Lucie, Schlötterer, Jörg, Welch, Charles
Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual perspectives, particularly in subjective tasks. In scenarios where anno
Externí odkaz:
http://arxiv.org/abs/2404.02340
Recent language models have been improved by the addition of external memory. Nearest neighbor language models retrieve similar contexts to assist in word prediction. The addition of locality levels allows a model to learn how to weight neighbors bas
Externí odkaz:
http://arxiv.org/abs/2311.00475
The potential to provide patients with faster information access while allowing medical specialists to concentrate on critical tasks makes medical domain dialog agents appealing. However, the integration of large-language models (LLMs) into these age
Externí odkaz:
http://arxiv.org/abs/2308.14641
We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low construct validity and reproducibility. Moreover, (3) emotional empath
Externí odkaz:
http://arxiv.org/abs/2210.16604
Recent language modeling performance has been greatly improved by the use of external memory. This memory encodes the context so that similar contexts can be recalled during decoding. This similarity depends on how the model learns to encode context,
Externí odkaz:
http://arxiv.org/abs/2210.15762
Instead of using a single ground truth for language processing tasks, several recent studies have examined how to represent and predict the labels of the set of annotators. However, often little or no information about annotators is known, or the set
Externí odkaz:
http://arxiv.org/abs/2210.14531
Studies on interpersonal conflict have a long history and contain many suggestions for conflict typology. We use this as the basis of a novel annotation scheme and release a new dataset of situations and conflict aspect annotations. We then build a c
Externí odkaz:
http://arxiv.org/abs/2208.08758
Large pre-trained neural language models have supported the effectiveness of many NLP tasks, yet are still prone to generating toxic language hindering the safety of their use. Using empathetic data, we improve over recent work on controllable text g
Externí odkaz:
http://arxiv.org/abs/2205.07233