27 citations · 69 across the 30 of their papers we have counts for
32 papers
Recognizing Dialogue Ambiguity via Candidate Set Visual Grounding
Shun Inadumi, Lee Sangmyeong, Koichiro Yoshino
Interpreting an ambiguous utterance in real-world interactions often requires context beyond a single utterance. When the utterance refers to objects in a visual scene, it is neces…
LaViSA: A Language and Vision Structural Ambiguity Benchmark
Lee Sangmyeong, Shun Inadumi, Koichiro Yoshino
Structural ambiguity arises when a single sentence admits multiple valid interpretations due to its syntactic structure, posing a fundamental challenge for language understanding.…
WarrantScore: Modeling Warrants between Claims and Evidence for Substantiation Evaluation in Peer Reviews
Kiyotada Mori, Shohei Tanaka, Tosho Hirasawa +3
The scientific peer-review process is facing a shortage of human resources due to the rapid growth in the number of submitted papers. The use of language models to reduce the human…
SciPostGen: Bridging the Gap between Scientific Papers and Poster Layouts
Shun Inadumi, Shohei Tanaka, Tosho Hirasawa +3
As the number of scientific papers continues to grow, there is a demand for approaches that can effectively convey research findings, with posters serving as a key medium for prese…
J-ORA: A Framework and Multimodal Dataset for Japanese Object Identification, Reference, Action Prediction in Robot Perception
Jesse Atuhurra, Hidetaka Kamigaito, Taro Watanabe +1
We introduce J-ORA, a novel multimodal dataset that bridges the gap in robot perception by providing detailed object attribute annotations within Japanese human-robot dialogue scen…
Pragmatic Theories Enhance Understanding of Implied Meanings in LLMs
Takuma Sato, Seiya Kawano, Koichiro Yoshino
The ability to accurately interpret implied meanings plays a crucial role in human communication and language use, and language models are also expected to possess this capability.…
Dialogue Response Prefetching Based on Semantic Similarity and Prediction Confidence of Language Model
Kiyotada Mori, Seiya Kawano, Angel Fernando Garcia Contreras +1
Prefetching of dialogue responses has been investigated to reduce user-perceived latency (UPL), which refers to the user's waiting time before receiving the system's response, in s…
What Do Humans Hear When Interacting? Experiments on Selective Listening for Evaluating ASR of Spoken Dialogue Systems
Kiyotada Mori, Seiya Kawano, Chaoran Liu +3
Spoken dialogue systems (SDSs) utilize automatic speech recognition (ASR) at the front end of their pipeline. The role of ASR in SDSs is to recognize information in user speech rel…
ASMR: Augmenting Life Scenario using Large Generative Models for Robotic Action Reflection
Shang-Chi Tsai, Seiya Kawano, Angel Garcia Contreras +2
When designing robots to assist in everyday human activities, it is crucial to enhance user requests with visual cues from their surroundings for improved intent understanding. Thi…
Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems
Shang-Chi Tsai, Yun-Nung Chen
With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…
Disambiguating Reference in Visually Grounded Dialogues through Joint Modeling of Textual and Multimodal Semantic Structures
Shun Inadumi, Nobuhiro Ueda, Koichiro Yoshino
Multimodal reference resolution, including phrase grounding, aims to understand the semantic relations between mentions and real-world objects. Phrase grounding between images and…
Proactive User Information Acquisition via Chats on User-Favored Topics
Shiki Sato, Jun Baba, Asahi Hentona +3
Chat-oriented dialogue systems designed to provide tangible benefits, such as sharing the latest news or preventing frailty in senior citizens, often require Proactive acquisition…
Training Dialogue Systems by AI Feedback for Improving Overall Dialogue Impression
Kai Yoshida, Masahiro Mizukami, Seiya Kawano +3
To improve user engagement during conversations with dialogue systems, we must improve individual dialogue responses and dialogue impressions such as consistency, personality, and…
ClaimBrush: A Novel Framework for Automated Patent Claim Refinement Based on Large Language Models
Seiya Kawano, Hirofumi Nonaka, Koichiro Yoshino
Automatic refinement of patent claims in patent applications is crucial from the perspective of intellectual property strategy. In this paper, we propose ClaimBrush, a novel framew…
LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs
LLM-jp, :, Akiko Aizawa +80
This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and stron…
Rapport-Driven Virtual Agent: Rapport Building Dialogue Strategy for Improving User Experience at First Meeting
Muhammad Yeza Baihaqi, Angel García Contreras, Seiya Kawano +1
Rapport is known as a conversational aspect focusing on relationship building, which influences outcomes in collaborative tasks. This study aims to establish human-agent rapport th…
J-CRe3: A Japanese Conversation Dataset for Real-world Reference Resolution
Nobuhiro Ueda, Hideko Habe, Yoko Matsui +5
Understanding expressions that refer to the physical world is crucial for such human-assisting systems in the real world, as robots that must perform actions that are expected by u…
A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions
Shun Inadumi, Seiya Kawano, Akishige Yuguchi +2
Situated conversations, which refer to visual information as visual question answering (VQA), often contain ambiguities caused by reliance on directive information. This problem is…
Whats New? Identifying the Unfolding of New Events in Narratives
Seyed Mahed Mousavi, Shohei Tanaka, Gabriel Roccabruna +3
Narratives include a rich source of events unfolding over time and context. Automatic understanding of these events provides a summarised comprehension of the narrative for further…
What Should the System Do Next?: Operative Action Captioning for Estimating System Actions
Taiki Nakamura, Seiya Kawano, Akishige Yuguchi +2
Such human-assisting systems as robots need to correctly understand the surrounding situation based on observations and output the required support actions for humans. Language is…
ARTA: Collection and Classification of Ambiguous Requests and Thoughtful Actions
Shohei Tanaka, Koichiro Yoshino, Katsuhito Sudoh +1
Human-assisting systems such as dialogue systems must take thoughtful, appropriate actions not only for clear and unambiguous user requests, but also for ambiguous user requests, e…
Reflection-based Word Attribute Transfer
Yoichi Ishibashi, Katsuhito Sudoh, Koichiro Yoshino +1
Word embeddings, which often represent such analogic relations as king - man + woman = queen, can be used to change a word's attribute, including its gender. For transferring king…
Caption Generation of Robot Behaviors based on Unsupervised Learning of Action Segments
Koichiro Yoshino, Kohei Wakimoto, Yuta Nishimura +1
Bridging robot action sequences and their natural language captions is an important task to increase explainability of human assisting robots in their recently evolving field. In t…
Conversational Response Re-ranking Based on Event Causality and Role Factored Tensor Event Embedding
Shohei Tanaka, Koichiro Yoshino, Katsuhito Sudoh +1
We propose a novel method for selecting coherent and diverse responses for a given dialogue context. The proposed method re-ranks response candidates generated from conversational…