In multi-party chat, it is common for multiple conversations to occur concurrently, leading to intermingled conversation threads in chat logs. In this work, we propose a novel Context-Aware Thread Detection (CATD) model that automatically disentangles these conversation threads. We evaluate our model on three real-world datasets and demonstrate an overall improvement in thread detection accuracy over state-of-the-art benchmarks.
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