RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation
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arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a memory entry, summary, typed record, or raw excerpt. We introduce RENDER, a benchmark control that fix…
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- 2026-08-26 04:00 · arXiv cs.AI
RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation