Papers by di Yin

2 papers
Collision to Cognition: Hash-Driven Graph Construction for Efficient RAG (2026.acl-long)

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Challenge: Retrieval-augmented generation (RAG) has been used for enhancing large language models with external knowledge.
Approach: They propose a framework for mining efficient graph structures via hashing to enhance RAG . they adopt an inductive paradigm where global graph structure emerges from local hash collisions .
Outcome: The proposed framework outperforms existing baselines while requiring no GPU resources or token budget.
Query-Aware Knowledge Retrieval via Hyperbolic Structuring (2026.acl-long)

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Challenge: Existing approaches focus primarily on retrieving isolated factual knowledge entities while neglecting the critical reasoning relationships.
Approach: They propose a query-centric retrieval framework that explicitly integrates structured knowledge graphs to support complex reasoning tasks.
Outcome: Extensive experiments on three benchmark datasets show that HyperRAG outperforms baselines.

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