Search Results for author: Hiromi Wakaki

Found 8 papers, 3 papers with code

Fundamental Exploration of Evaluation Metrics for Persona Characteristics of Text Utterances

no code implementations SIGDIAL (ACL) 2021 Chiaki Miyazaki, Saya Kanno, Makoto Yoda, Junya Ono, Hiromi Wakaki

When evaluating the appropriateness of a large number of arbitrary utterances to be registered in the utterance database of a retrieval-based dialog system, evaluation metrics that require a reference (or a “correct” utterance) for each evaluation target cannot be used.


Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning

no code implementations23 Mar 2024 Zhouhang Xie, Bodhisattwa Prasad Majumder, Mengjie Zhao, Yoshinori Maeda, Keiichi Yamada, Hiromi Wakaki, Julian McAuley

We consider the task of building a dialogue system that can motivate users to adopt positive lifestyle changes: Motivational Interviewing.

Instruction Following

DiffuCOMET: Contextual Commonsense Knowledge Diffusion

1 code implementation26 Feb 2024 Silin Gao, Mete Ismayilzada, Mengjie Zhao, Hiromi Wakaki, Yuki Mitsufuji, Antoine Bosselut

Inferring contextually-relevant and diverse commonsense to understand narratives remains challenging for knowledge models.

Using Natural Language Inference to Improve Persona Extraction from Dialogue in a New Domain

no code implementations12 Jan 2024 Alexandra DeLucia, Mengjie Zhao, Yoshinori Maeda, Makoto Yoda, Keiichi Yamada, Hiromi Wakaki

To address both these issues, we introduce a natural language inference method for post-hoc adapting a trained persona extraction model to a new setting.

Natural Language Inference

Towards reporting bias in visual-language datasets: bimodal augmentation by decoupling object-attribute association

no code implementations2 Oct 2023 Qiyu Wu, Mengjie Zhao, Yutong He, Lang Huang, Junya Ono, Hiromi Wakaki, Yuki Mitsufuji

In this paper, we focus on the wide existence of reporting bias in visual-language datasets, embodied as the object-attribute association, which can subsequentially degrade models trained on them.

Attribute Object

PeaCoK: Persona Commonsense Knowledge for Consistent and Engaging Narratives

1 code implementation3 May 2023 Silin Gao, Beatriz Borges, Soyoung Oh, Deniz Bayazit, Saya Kanno, Hiromi Wakaki, Yuki Mitsufuji, Antoine Bosselut

They must also learn to maintain consistent speaker personas for themselves throughout the narrative, so that their counterparts feel involved in a realistic conversation or story.

Knowledge Graphs World Knowledge

ComFact: A Benchmark for Linking Contextual Commonsense Knowledge

1 code implementation23 Oct 2022 Silin Gao, Jena D. Hwang, Saya Kanno, Hiromi Wakaki, Yuki Mitsufuji, Antoine Bosselut

Understanding rich narratives, such as dialogues and stories, often requires natural language processing systems to access relevant knowledge from commonsense knowledge graphs.

Knowledge Graphs Response Generation +1

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