14 citations · 42 across the 15 of their papers we have counts for
5 papers · 1 filter
Open World Classification with Adaptive Negative Samples
Ke Bai, Guoyin Wang, Jiwei Li +5
Open world classification is a task in natural language processing with key practical relevance and impact. Since the open or {\em unknown} category data only manifests in the infe…
Ranking-Enhanced Unsupervised Sentence Representation Learning
Yeon Seonwoo, Guoyin Wang, Changmin Seo +6
Unsupervised sentence representation learning has progressed through contrastive learning and data augmentation methods such as dropout masking. Despite this progress, sentence enc…
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
Boseop Kim, HyoungSeok Kim, Sang-Woo Lee +34
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less report…
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration
Han Li, Sunghyun Park, Aswarth Dara +5
Current state-of-the-art large-scale conversational AI or intelligent digital assistant systems in industry comprises a set of components such as Automatic Speech Recognition (ASR)…
A scalable framework for learning from implicit user feedback to improve natural language understanding in large-scale conversational AI systems
Sunghyun Park, Han Li, Ameen Patel +5
Natural Language Understanding (NLU) is an established component within a conversational AI or digital assistant system, and it is responsible for producing semantic understanding…