activity
20152022
most citedLarge-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation

7 citations · 39 across the 15 of their papers we have counts for

collaborators

18 papers

cs.CL20225 cited

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…

cs.CL20221 cited

Continuous Decomposition of Granularity for Neural Paraphrase Generation

Xiaodong Gu, Zhaowei Zhang, Sang-Woo Lee +2

While Transformers have had significant success in paragraph generation, they treat sentences as linear sequences of tokens and often neglect their hierarchical information. Prior…

cs.CV20227 cited

Mutual Information Divergence: A Unified Metric for Multimodal Generative Models

Jin-Hwa Kim, Yunji Kim, Jiyoung Lee +2

Text-to-image generation and image captioning are recently emerged as a new experimental paradigm to assess machine intelligence. They predict continuous quantity accompanied by th…

cs.CL2022

Two-Step Question Retrieval for Open-Domain QA

Yeon Seonwoo, Juhee Son, Jiho Jin +4

The retriever-reader pipeline has shown promising performance in open-domain QA but suffers from a very slow inference speed. Recently proposed question retrieval models tackle thi…

cs.CL2022

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…

cs.CL20221 cited

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…