SpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue
SpeakerMem-R1 uses dual-track speaker memory to improve multi-party dialogue recall across GroupMem, SocialMem, and EverMem benchmarks.
SpeakerMem-R1 keeps speaker-labeled verbatim messages and derived person- and group-level states, then joins evidence by entity, event, and time. Writer-R1 is trained with SpeakerLevenshtein and speaker-conditioned GRPO to reduce attribution and update errors for local deployment. Binary accuracies are 47.9% on GroupMemBench, 69.2% on SocialMemBench, and 61.9% on EverMemBench, with 62.33% on the public EverMemBench leaderboard. It scores 70.85% on 1,986 LoCoMo questions, and reinforcement learning raises a 305-question set from 57.38% to 68.20%.
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