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LMEB: Long-horizon Memory Embedding Benchmark
Embedding models are increasingly used as retrievers in memory-augmented systems, but are typically evaluated on traditional passage retrieval benchmarks. It remains unclear whether models that excel at passage retrieval can retrieve fragmented, context-dependent, and temporally distant memories. To
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