Verified75% confidenceFactExact time
Conversational recall benchmarks such as LoCoMo and LongMemEval measure question-answering ability over conversation history, rather than whether memory has changed the actual behavior of tool-using agents.
3
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75%
Confidence
Long-term
Relevance
9/11/2026
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UnverifiedLongMemEval is a public benchmark for evaluating long-term memory systems, constructing chat histories of about 50 conversation segments, with questions divided into dimensions such as knowledge updates, temporal reasoning, multi-session reasoning, assistant memory and user memory, and judging performed by an LLM via semantic comparison based on the official prompt.79% similarUnverifiedProduction-grade agents need to distinguish between short-term memory (current session context) and long-term memory (cross-session user preferences and historical facts).79% similarUnverifiedTwo default practices for long-term memory: extraction should be placed asynchronously outside the reply path (because the facts of this conversation are already in this session's history); take a snapshot of memory at the start of each conversation (the memory block is placed before the history, and updating it midway would break the cache).76% similarUnverifiedLocomo (Long-Context Memory) focuses on evaluating cross-session contextual coherence and temporal reasoning76% similarUnverifiedLong-term memory evaluation benchmarks (such as LongMemEval and the MemGPT benchmark) assess five dimensions: single-hop information extraction, cross-session reasoning, knowledge updating, temporal reasoning, and abstention judgment.75% similar
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