DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities

• URL: http://arxiv.org/abs/2507.05750v1
• Date: Tue, 08 Jul 2025 07:52:12 GMT
• Title: DocTalk: Scalable Graph-based Dialogue Synthesis for Enhancing LLM Conversational Capabilities
• Authors: Jing Yang Lee, Hamed Bonab, Nasser Zalmout, Ming Zeng, Sanket Lokegaonkar, Colin Lockard, Binxuan Huang, Ritesh Sarkhel, Haodong Wang,
• Abstract summary: We introduce a novel approach to address this discrepancy by synthesizing conversational data from existing text corpora.<n>Applying our pipeline to Wikipedia articles, we curate DocTalk, a multi-turn pre-training dialogue corpus consisting of over 730k long conversations.<n>We show that incorporating DocTalk during pre-training results in up to 40% gain in context memory and understanding, without compromising base performance.
• Score: 13.615473441588009
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) are increasingly employed in multi-turn conversational tasks, yet their pre-training data predominantly consists of continuous prose, creating a potential mismatch between required capabilities and training paradigms. We introduce a novel approach to address this discrepancy by synthesizing conversational data from existing text corpora. We present a pipeline that transforms a cluster of multiple related documents into an extended multi-turn, multi-topic information-seeking dialogue. Applying our pipeline to Wikipedia articles, we curate DocTalk, a multi-turn pre-training dialogue corpus consisting of over 730k long conversations. We hypothesize that exposure to such synthesized conversational structures during pre-training can enhance the fundamental multi-turn capabilities of LLMs, such as context memory and understanding. Empirically, we show that incorporating DocTalk during pre-training results in up to 40% gain in context memory and understanding, without compromising base performance. DocTalk is available at https://huggingface.co/datasets/AmazonScience/DocTalk.

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