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The memory capabilities of Large Language Models (LLMs) have garnered increasing attention recently. Despite great success achieved, existing retrieval-based memory approaches typically overlook the differences between memories and employ a unified strategy to process all memories, leading to suboptimal performance. Th...
Inspired by Multiple-Trace Theory in cognitive psychology, this work revisit long video understanding from a probe-echo perspective, in which human episodic memories are activated and integrated in parallel, and proposes ProEchoMem, a cognitive-inspired framework that simulates the probe-echo mechanism.
A lightweight training framework that learns a single Behavior-Equivalent Token that substantially reduces inference cost and frees nearly the entire context window for user inputs and model outputs.
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