LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation
This addresses a lack of resources for creating multi-party conversations, primarily for researchers or developers needing such data, but it is incremental as it builds on existing debate structures and LLM tools.
The authors tackled the problem of creating multi-party conversations from existing debate trees by developing LLMberjack, a platform that uses interactive tree visualization and optional LLM assistance to produce coherent dialogue sequences, reducing human effort and enhancing output quality.
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.