Prompt learning has been proven to be highly effective in improving
pre-...
Recent works demonstrate a remarkable ability to customize text-to-image...
Keyword spotting systems continuously process audio streams to detect
ke...
The ability to accurately locate and navigate to a specific object is a
...
The recently proposed Vision transformers (ViTs) have shown very impress...
Factorizing a large matrix into small matrices is a popular strategy for...
Learning to answer visual questions is a challenging task since the
mult...
Domain classification is the fundamental task in natural language
unders...
Pre-trained language models such as BERT have shown remarkable effective...
Moving beyond testing on in-distribution data works on Out-of-Distributi...
Intent classification is a major task in spoken language understanding (...
One major task of spoken language understanding (SLU) in modern personal...
Existing open-domain dialogue generation models are usually trained to m...
Text-based interactive recommendation provides richer user feedback and ...
Location privacy has been extensively studied in the literature. However...
Deep neural networks have attained remarkable performance when applied t...
Recurrent neural network (RNN) based joint intent classification and slo...
With the rapid development in deep learning, deep neural networks have b...
Many vision and language models suffer from poor visual grounding - ofte...
Intent detection and slot filling are two main tasks for building a spok...
With the recent surge of interests in deep neural networks, more real-wo...
Semantic frame parsing is a crucial component in spoken language
underst...
Learning intents and slot labels from user utterances is a fundamental s...
Humans are able to understand and perform complex tasks by strategically...