no code implementations • 19 Mar 2024 • Shiki Sato, Reina Akama, Jun Suzuki, Kentaro Inui
In this paper, we build a large dataset of response generation models' contradictions for the first time.
no code implementations • 19 Nov 2022 • Shiki Sato, Yosuke Kishinami, Hiroaki Sugiyama, Reina Akama, Ryoko Tokuhisa, Jun Suzuki
Automation of dialogue system evaluation is a driving force for the efficient development of dialogue systems.
1 code implementation • COLING 2022 • Yosuke Kishinami, Reina Akama, Shiki Sato, Ryoko Tokuhisa, Jun Suzuki, Kentaro Inui
Prior studies addressing target-oriented conversational tasks lack a crucial notion that has been intensively studied in the context of goal-oriented artificial intelligence agents, namely, planning.
1 code implementation • SIGDIAL (ACL) 2022 • Shiki Sato, Reina Akama, Hiroki Ouchi, Ryoko Tokuhisa, Jun Suzuki, Kentaro Inui
In this scenario, the quality of the n-best list considerably affects the occurrence of contradictions because the final response is chosen from this n-best list.
1 code implementation • ACL 2020 • Shiki Sato, Reina Akama, Hiroki Ouchi, Jun Suzuki, Kentaro Inui
Existing automatic evaluation metrics for open-domain dialogue response generation systems correlate poorly with human evaluation.