Papers by Shaowen Chen

2 papers
AED-RAG: Continuous Multi-Granular Context Fusion for Retrieval-Augmented Generation via Adaptive Ensemble Decoding (2026.findings-acl)

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Challenge: Existing alignment strategies that rely on discrete reranking struggle to address this granularity mismatch or effectively balance external evidence with internal knowledge.
Approach: They propose a framework that synergizes discrete retrieval with continuous reranking to discern the information density differences between unstructured narrative passages and structured knowledge triplets.
Outcome: Extensive experiments on four open-domain QA benchmarks show that AED-RAG significantly outperforms competitive baselines.
GAM: Hierarchical Graph-based Agentic Memory for LLM Agents (2026.acl-long)

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Challenge: Current unified stream-based memory systems facilitate context updates but remain vulnerable to interference from transient noise.
Approach: They propose a hierarchical Graph-based Agentic Memory framework that explicitly decouples memory encoding from consolidation to resolve conflict between rapid context perception and stable knowledge retention.
Outcome: The proposed framework outperforms state-of-the-art benchmarks on LoCoMo and LongDialQA.

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