Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Large language models (LLMs) are used to generate content for a wide range of tasks, and
are set to reach a growing audience in coming years due to integration in product interfaces …

In natural language processing (NLP), the" Transformer" architecture was proposed as the
first transduction model replying entirely on self-attention mechanisms without using …

We aim to leverage human and machine intelligence together for attention supervision.
Specifically, we show that human annotation cost can be kept reasonably low, while its …

A large-scale conversational agent can suffer from understanding user utterances with
various ambiguities such as ASR ambiguity, intent ambiguity, and hypothesis ambiguity …

In large-scale domain classification, an utterance can be handled by multiple domains with
overlapped capabilities. However, only a limited number of ground-truth domains are …

Neural attention mechanism has been used as a form of explanation for model behavior.
Users can either passively consume explanation or actively disagree with explanation and …

Deep Learning has revolutionized the whole discipline of machine learning, heavily
impacting fields such as Computer Vision, Natural Language Processing, and other …

In this modern world, due to the increased mobility of humans, encountering a foreign
language has become a common challenge for many people around the world. This causes …