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A new process-level latent variable model (PLVM) predicts future behavioral strategies from partial process traces across tasks, demonstrated in PowerWash Simulator gameplay data.
This paper empirically tests the psychometric reliability of LLM-based user state classification, finding that only 31 of 213 metrics met reliability criteria, questioning trust in real-time adaptive systems.
EvolveMem introduces a self-evolving memory architecture for LLM agents that optimizes retrieval configurations through LLM-powered diagnosis and iterative research cycles, achieving significant performance improvements on benchmarks like LoCoMo and MemBench.