Add ComoRAG (AAAI'26) to Hybrid GraphRAG and Multi-round Retriever#23
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EternityJune25 wants to merge 2 commits into
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Add ComoRAG (AAAI'26) to Hybrid GraphRAG and Multi-round Retriever#23EternityJune25 wants to merge 2 commits into
EternityJune25 wants to merge 2 commits into
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Add [ComoRAG](https://ojs.aaai.org/index.php/AAAI/article/view/40644)(AAAI 2026) to two categories: 1. **Hybrid GraphRAG** — ComoRAG organizes knowledge into three complementary layers: Veridical Layer (raw text + LLM-extracted knowledge triples with entity linking), Semantic Layer (hierarchical summaries via RAPTOR clustering), and Episodic Layer (narrative flow summaries). This combines textual and relational knowledge sources. 2. **Multi-round Retriever** — The core innovation is a Metacognitive Control Loop (Self-Probe → Tri-Retrieve → Mem-Encode → Mem-Fuse → Try-Answer) enabling stateful, iterative retrieval and reasoning across multiple rounds with a dynamic memory workspace. ComoRAG achieves consistent relative gains up to 11% on four long-narrative benchmarks (200K+ tokens). **Paper:** https://doi.org/10.1609/aaai.v40i39.40644
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Add ComoRAG (AAAI 2026) to two categories:
1. Hybrid GraphRAG
Combines textual and relational knowledge sources. Achieves consistent relative gains up to 11% on four long-narrative benchmarks (200K+ tokens).
Paper
2. Multi-round Retriever
Self-Probe → Tri-Retrieve → Mem-Encode → Mem-Fuse → Try-AnswerEnables stateful, iterative retrieval and reasoning across multiple rounds with a dynamic memory workspace.
Achieves consistent relative gains up to 11% on four long-narrative benchmarks (200K+ tokens).
Paper