Deterministic agentic-style multi-hop RAG at research-SOTA parity on commodity LLM APIs — no GPU, proof tree per answer.
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Updated
Jun 23, 2026 - Python
Deterministic agentic-style multi-hop RAG at research-SOTA parity on commodity LLM APIs — no GPU, proof tree per answer.
7-layer RAG framework that eliminates semantic drift + context poisoning. Faithfulness 0.94 vs 0.71 Naive RAG. +13.6 EM on multi-hop QA.
Binary evidence-sufficiency dissociation in reasoning-model hidden states for fixed-question, changed-context multi-hop QA.
Knowledge-graph RAG for multi-hop QA: a controlled study that overturned its own +8.8 win under realistic evaluation.
A fine-tuned Qwen2.5-1.5B model that breaks complex multi-hop questions into atomic sub-queries with dependency graphs, doubling RAG retrieval accuracy in ~50ms
Local-only, graph-augmented, iteratively-reasoning, self-corrective RAG showcase on Apple Silicon — pushing toward published SOTA on multi-hop QA (MuSiQue, 2WikiMultiHopQA, HotpotQA) with HippoRAG 2 + Adaptive routing + Search-o1 iterative reasoning + CRAG-style gating + NLI faithfulness verification.
Knowledge-graph RAG library for multi-hop QA — iterative retrieve-and-reason (IRCoT), graph retrieval, and cross-document enrichment at ingest. Production retrieval pipeline in Python.
Official implementation of CHARM: Cascading Hallucination Aware Resolution and Mitigation for multi-step agentic RAG pipelines.
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