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TransMem

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2026-08-03 / skill-finderTurn discarded hidden states into an agent memory substrate: MemoryAgentBench accuracy jumps 29.54% to 40.00% with no context reprocessingTransMem is a lightweight parametric module that converts sparse historical hidden states into reusable memory representations, using a gating network to intervene dynamically on current hidden states — all at inference time, without reprocessing prior context. Training uses evidence-conditioned self-distillation, where a memory-augmented student sees full context while matching an evidence-only teacher sharing the same frozen backbone. Reported gains are large across three benchmarks: 11.58–29.25 F1 points on LoCoMo, 10.20–13.03 F1 on HotpotQA, and 29.54% to 40.00% accuracy on MemoryAgentBench.

Source trail

arXiv 2607.29032

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