Evaluating Compressed Memory: Dependence, Utility, and Content Benefit
Does a language model answer better because its compressed memory contains useful document information? Replacing memory vectors with zeros can lower a trained model's score without showing that it outperforms a model trained without memory.
By Minsu Oh, Seunghui Jwa, Chanjun Park, Yeo-Chan YoonarXiv - cs.CL (NLP)
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Originally published by arXiv - cs.CL (NLP) on Oct 15, 2026.
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