Papers by Zongsheng Cao

2 papers
FlowRAG: Synergizing Explicit Reasoning via Frequency-Aware Multi-Granularity Graph Flow (2026.findings-acl)

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Challenge: Existing methods for Graph-based retrieval-augmented generation rely on implicit semantic relevance propagation.
Approach: They propose a semantic-aware retrieval framework that improves both semantic recall and explicit reasoning.
Outcome: Extensive experiments show that FlowRAG improves both semantic recall and explicit reasoning.
FlowSearch: Advancing Deep Research with Dynamic Structured Knowledge Flow (2026.acl-long)

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Challenge: FlowSearch is a multi-agent framework that actively constructs and evolves a dynamic structured knowledge flow to drive subtask execution and reasoning.
Approach: They propose a multi-agent framework that actively constructs and evolves a dynamic structured knowledge flow to drive subtask execution and reasoning.
Outcome: The proposed framework achieves competitive performance on GAIA, HLE, GPQA and TRQA benchmarks and is available to download.

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