SelRoute routes queries to type-specific retrieval pipelines, achieving Recall@5 of 0.800 with a 109M model on LongMemEval_M and outperforming LLM-augmented baselines including a strong zero-ML lexical method.
Preprint, arXiv:2501.13121
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A survey of evaluation methods for LLM-based agents from five perspectives, identifying trends toward realistic benchmarks and gaps in safety, cost-efficiency, and robustness.
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SelRoute: Query-Type-Aware Routing for Long-Term Conversational Memory Retrieval
SelRoute routes queries to type-specific retrieval pipelines, achieving Recall@5 of 0.800 with a 109M model on LongMemEval_M and outperforming LLM-augmented baselines including a strong zero-ML lexical method.
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Survey on Evaluation of LLM-based Agents
A survey of evaluation methods for LLM-based agents from five perspectives, identifying trends toward realistic benchmarks and gaps in safety, cost-efficiency, and robustness.