Neuro-symbolic sentiment analysis with dynamic word sense disambiguation
Sentiment analysis is a task that highly depends on the understanding of word senses.
Traditional neural network models are black boxes that represent word senses as vectors …
Traditional neural network models are black boxes that represent word senses as vectors …
Reducing disambiguation biases in NMT by leveraging explicit word sense information
Recent studies have shed some light on a common pitfall of Neural Machine Translation
(NMT) models, stemming from their struggle to disambiguate polysemous words without …
(NMT) models, stemming from their struggle to disambiguate polysemous words without …
Bringing humans at the epicenter of artificial intelligence: A confluence of AI, HCI and human centered computing
Abstract Artificial Intelligence (AI) and Human Computer Interaction (HCI) often intersect
under the purview of different technologies in a plethora of application areas, wherein it …
under the purview of different technologies in a plethora of application areas, wherein it …
Disentangling syntactics, semantics, and pragmatics in natural language processing
X Zhang - 2024 - dr.ntu.edu.sg
In the era of deep learning, the natural language processing (NLP) community has become
increasingly reliant on large language models (LLM), which are essentially probabilistic …
increasingly reliant on large language models (LLM), which are essentially probabilistic …