4 accepted papers
The prevalence of the powerful multilingual models, such as Whisper, has significantly advanced the researches on speech recognition. However, these models often struggle with handling the code-switching setting, which is essential in multilingual speech recognition. Recent studies have attempted to…
The advent of large language models (LLMs), such as GPT 3.5, has demonstrated significant potential, especially when paired with the prompt engineering techniques. However, while this setting excels in zero-shot or few-shot scenario, the direct utilization of LLMs in multi-domain task-oriented dialo…
The prompt-based learning, as used in GPT-3, has become a popular approach to extract knowledge from a powerful pre-trained language model (PLM) for natural language understanding tasks. However, either applying the hard prompt for sentences by defining a collection of human-engineering prompt templ…
This paper presents a new language processing and understanding where an adaptive data augmentation strategy for individual documents is proposed instead of using one universal policy for the whole dataset. Importantly, a reinforcement learning and understanding method is exploited for document clas…