5 citations · 10 across the 5 of their papers we have counts for
5 papers
Can Current Task-oriented Dialogue Models Automate Real-world Scenarios in the Wild?
Sang-Woo Lee, Sungdong Kim, Donghyeon Ko +9
Task-oriented dialogue (TOD) systems are mainly based on the slot-filling-based TOD (SF-TOD) framework, in which dialogues are broken down into smaller, controllable units (i.e., s…
Keep Me Updated! Memory Management in Long-term Conversations
Sanghwan Bae, Donghyun Kwak, Soyoung Kang +7
Remembering important information from the past and continuing to talk about it in the present are crucial in long-term conversations. However, previous literature does not deal wi…
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model
Seongjin Shin, Sang-Woo Lee, Hwijeen Ahn +8
Many recent studies on large-scale language models have reported successful in-context zero- and few-shot learning ability. However, the in-depth analysis of when in-context learni…
Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Models
Sanghwan Bae, Donghyun Kwak, Sungdong Kim +4
Recent open-domain dialogue models have brought numerous breakthroughs. However, building a chat system is not scalable since it often requires a considerable volume of human-human…
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…