Agent memory stops ranking by similarity alone: TrawMem assigns task roles, lifting LoCoMo judge scores by about 4 points
Agent memory systems typically retrieve memories by relevance to the current query and use them as contextual evidence; TrawMem instead organizes interaction histories into local threads, then assigns task-oriented roles and jointly selects complementary memories to build a task workspace. Across LoCoMo and MemGallery with four open- and closed-source backbones, macro-F1 improves by 2.23 to 3.14 points over representative memory systems; on LoCoMo, LLM-Judge scores rise by 4.07 and 4.31 percentage points over SimpleMem on Qwen3.5-9B and DeepSeek-V4-Flash, with roughly 12.8% and 5.1% fewer context tokens.