MEMPROBE: Probing Long-Term Agent Memory via Hidden User-State Recovery
Long-term memory in LLM agents should be evaluated as an auditable post-interaction artifact by reconstructing structured user state from the agent's memory, as demonstrated by MEM…
Hugging Face · Daily Papers
·Enze Ma, Yufan Zhou
·
·▲ 1 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Enze Ma, Yufan Zhou, Wei-Chieh Huang, Jie Yang, Huanhuan Ma, Zixuan Wang
- 1 upvotes da comunidade
- Temas: long-term memory, LLM agents, auditable post-interaction artifact, memory recovery, MEMPROBE, synthetic ground truth
Resumo
Resumo original (em inglês), extraído do paper:
Long-term memory in LLM agents should be evaluated as an auditable post-interaction artifact by reconstructing structured user state from the agent's memory, as demonstrated by MEMPROBE, a benchmark testing memory recovery against synthetic ground truth across 50 simulated users with 31 hidden dimensions each.