Papers with long-term dialogue scenarios

1 papers
H-MEM: Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents (2026.eacl-long)

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Challenge: Long-term memory is one of the key factors influencing the reasoning capabilities of Large Language Model Agents.
Approach: They propose a hierarchical memory architecture that organizes and updates memory in a multi-level fashion based on the degree of semantic abstraction.
Outcome: The proposed model outperforms baseline methods on five task settings from the LoCoMo dataset.

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