Papers by Zhengkang Guo
Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human–Agent Interaction (2026.acl-long)
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Zisu Huang, Muzhao Tian, Xiaohua Wang, Jingwen Xu, Zhengkang Guo, Qi Qian, Kaitao Song, Jiakang Yuan, Changze Lv, Xiaoqing Zheng
| Challenge: | Existing systems that use memory as an "all-or-nothing" approach to memory usage are often static and rely on experience-following tendencies. |
| Approach: | They propose a framework that allows users to dynamically regulate memory reliance by adding context into the model's prompt. |
| Outcome: | The proposed model outperforms prompting and memory masking strategies in multiple scenarios. |