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Found 6 papers, 1 papers with code
Every time I fire a conversational designer, the performance of the dialogue system goes down
In fact, rules from conversational designers used in CLINN significantly outperform a state-of-the-art neural-based dialogue system when trained with smaller sets of annotated dialogues.
Change My Mind: How Syntax-based Hate Speech Recognizer Can Uncover Hidden Motivations Based on Different Viewpoints
Hate speech recognizers may mislabel sentences by not considering the different opinions that society has on selected topics.
Less is KEN: a Universal and Simple Non-Parametric Pruning Algorithm for Large Language Models
This approach maintains model performance while allowing storage of only the optimized subnetwork, leading to significant memory savings.
Exploring Linguistic Properties of Monolingual BERTs with Typological Classification among Languages
The impressive achievements of transformers force NLP researchers to delve into how these models represent the underlying structure of natural language.
Every time I fire a conversational designer, the performance of the dialog system goes down
Incorporating explicit domain knowledge into neural-based task-oriented dialogue systems is an effective way to reduce the need of large sets of annotated dialogues.
Lacking the embedding of a word? Look it up into a traditional dictionary
In this paper, we propose to use definitions retrieved in traditional dictionaries to produce word embeddings for rare words.
