EMA: An Episodic Memory Agent for Efficient and Selective Memory (2026.findings-acl)
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| Challenge: | Existing memory-augmented methods often incorporate full dialog histories without filtering, resulting in information redundancy and inference latency. |
| Approach: | They propose a framework that abstracts conversational context into Episodic Memory Units (EMUs) they propose EMA, MemDecider and a filtering decision module to reduce noise and improve overall performance. |
| Outcome: | The proposed framework reduces token consumption by 11.48% while improving performance on two widely-used benchmarks. |
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