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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2601.04135 |
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| _version_ | 1866917188533747712 |
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| author | Bottona, Leonardo Penzo, Nicolò Lepri, Bruno Guerini, Marco Tonelli, Sara |
| author_facet | Bottona, Leonardo Penzo, Nicolò Lepri, Bruno Guerini, Marco Tonelli, Sara |
| contents | We present LLMberjack, a platform for creating multi-party conversations starting from existing debates, originally structured as reply trees. The system offers an interactive interface that visualizes discussion trees and enables users to construct coherent linearized dialogue sequences while preserving participant identity and discourse relations. It integrates optional large language model (LLM) assistance to support automatic editing of the messages and speakers' descriptions. We demonstrate the platform's utility by showing how tree visualization facilitates the creation of coherent, meaningful conversation threads and how LLM support enhances output quality while reducing human effort. The tool is open-source and designed to promote transparent and reproducible workflows to create multi-party conversations, addressing a lack of resources of this type. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_04135 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation Bottona, Leonardo Penzo, Nicolò Lepri, Bruno Guerini, Marco Tonelli, Sara Computation and Language Human-Computer Interaction We present LLMberjack, a platform for creating multi-party conversations starting from existing debates, originally structured as reply trees. The system offers an interactive interface that visualizes discussion trees and enables users to construct coherent linearized dialogue sequences while preserving participant identity and discourse relations. It integrates optional large language model (LLM) assistance to support automatic editing of the messages and speakers' descriptions. We demonstrate the platform's utility by showing how tree visualization facilitates the creation of coherent, meaningful conversation threads and how LLM support enhances output quality while reducing human effort. The tool is open-source and designed to promote transparent and reproducible workflows to create multi-party conversations, addressing a lack of resources of this type. |
| title | LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation |
| topic | Computation and Language Human-Computer Interaction |
| url | https://arxiv.org/abs/2601.04135 |