no code implementations • 20 Dec 2022 • Sang-Woo Lee, Sungdong Kim, Donghyeon Ko, Donghoon Ham, Youngki Hong, Shin Ah Oh, Hyunhoon Jung, Wangkyo Jung, Kyunghyun Cho, Donghyun Kwak, Hyungsuk Noh, WooMyoung Park
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., slots) to fulfill a specific task.
no code implementations • 17 Oct 2022 • Sanghwan Bae, Donghyun Kwak, Soyoung Kang, Min Young Lee, Sungdong Kim, Yuin Jeong, Hyeri Kim, Sang-Woo Lee, WooMyoung Park, Nako Sung
Remembering important information from the past and continuing to talk about it in the present are crucial in long-term conversations.
1 code implementation • NAACL 2022 • Sanghwan Bae, Donghyun Kwak, Sungdong Kim, Donghoon Ham, Soyoung Kang, Sang-Woo Lee, WooMyoung Park
In this work, we study the challenge of imposing roles on open-domain dialogue systems, with the goal of making the systems maintain consistent roles while conversing naturally with humans.
no code implementations • NAACL 2022 • Seongjin Shin, Sang-Woo Lee, Hwijeen Ahn, Sungdong Kim, HyoungSeok Kim, Boseop Kim, Kyunghyun Cho, Gichang Lee, WooMyoung Park, Jung-Woo Ha, Nako Sung
Many recent studies on large-scale language models have reported successful in-context zero- and few-shot learning ability.
2 code implementations • EMNLP 2021 • Boseop Kim, HyoungSeok Kim, Sang-Woo Lee, Gichang Lee, Donghyun Kwak, Dong Hyeon Jeon, Sunghyun Park, Sungju Kim, Seonhoon Kim, Dongpil Seo, Heungsub Lee, Minyoung Jeong, Sungjae Lee, Minsub Kim, Suk Hyun Ko, Seokhun Kim, Taeyong Park, Jinuk Kim, Soyoung Kang, Na-Hyeon Ryu, Kang Min Yoo, Minsuk Chang, Soobin Suh, Sookyo In, Jinseong Park, Kyungduk Kim, Hiun Kim, Jisu Jeong, Yong Goo Yeo, Donghoon Ham, Dongju Park, Min Young Lee, Jaewook Kang, Inho Kang, Jung-Woo Ha, WooMyoung Park, Nako Sung
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data.
no code implementations • 6 Jul 2017 • HyoungSeok Kim, JiHoon Kang, WooMyoung Park, SukHyun Ko, YoonHo Cho, DaeSung Yu, YoungSook Song, JungWon Choi
The regret bound of an optimization algorithms is one of the basic criteria for evaluating the performance of the given algorithm.