Papers with memory components
How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior (2026.acl-long)
Copied to clipboard
Zidi Xiong, Yuping Lin, Wenya Xie, Pengfei He, Zirui Liu, Jiliang Tang, Himabindu Lakkaraju, Zhen Xiang
| Challenge: | In practice, memory designs vary widely across agents due to their diverse objectives and functionalities. |
| Approach: | They conduct an empirical study on how memory management choices impact the LLM agents’ behavior, especially their long-term performance. |
| Outcome: | The proposed methods show that LLM agents display an experience-following property, which results in highly similar agent outputs. |
Document Context Neural Machine Translation with Memory Networks (P18-1)
Copied to clipboard
| Challenge: | Experimental results show that our model exploits both source and target document context. |
| Approach: | They propose a document-level neural machine translation model which takes both source and target document context into account using memory networks. |
| Outcome: | The proposed model outperforms previous work in terms of BLEU and METEOR in English translations. |
Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning (D19-1)
Copied to clipboard
| Challenge: | Existing methods for learning knowledge Graphs are incomplete and therefore need well-pretraining. |
| Approach: | They propose a deep reinforcement learning based model which incorporates LSTM and Graph Attention Mechanism as the memory components. |
| Outcome: | The proposed model can get rid of the pretraining process and achieve state-of-the-art performance compared with the other models. |