Papers with reasoning phase
H-MEM: Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents (2026.eacl-long)
Copied to clipboard
| 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. |