HyperSumm-RL: A Dialogue Summarization Framework for Modeling Leadership Perception in Social Robots
This paper introduces HyperSumm-RL, a hypertext-aware summarization and interaction analysis framework designed to investigate human perceptions of social robot leadership through long-form dialogue. The system utilizes a structured Natural Language Processing (NLP) workflow that combines transforme- doi
- 10.1145/3720553.3746685
- isbn
- 979-8-4007-1534-1
- name
- HyperSumm-RL: A Dialogue Summarization Framework for Modeling Leadership Perception in Social Robots
- pages
- 171–176
- source
- BITS XML + supplied PDF
- acm_url
- https://dl.acm.org/doi/10.1145/3720553.3746685
- authors
- Subasish Das
- doi_url
- https://doi.org/10.1145/3720553.3746685
- license
- © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
- summary
- This paper introduces HyperSumm-RL, a hypertext-aware summarization and interaction analysis framework designed to investigate human perceptions of social robot leadership through long-form dialogue. The system utilizes a structured Natural Language Processing (NLP) workflow that combines transforme
- keywords
- social robot, leadership perception, text summarization, DialogLM
- arxiv_url
- https://arxiv.org/abs/2507.04160
- published
- 2025-09-15
- conference
- HT '25: 36th ACM Conference on Hypertext and Social Media, Chicago, IL, USA, September 15-19, 2025
- open_access
- false
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- https://dl.acm.org/doi/full/10.1145/3720553.3746685
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- (empty)
- displayAuthor
- Subasish Das
- proceedings_url
- https://dl.acm.org/doi/proceedings/10.1145/3720553
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- 2025-09-15
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