Is MMGraphRAG superseded?

MMGraphRAG (Retrieval-augmented generation): superseded — cited as a baseline and beaten by newer methods. 2 paper(s) critique it, 2 beat it on benchmarks — #52 of 1179 most-superseded. Sub-problem: cluster led by MMGraphRAG. Newer alternatives in the same sub-problem include VideoStir, Graph-to-Frame RAG, MG²-RAG, AutoThinkRAG, AgenticOCR.

Retrieval-augmented generation

MMGraphRAG

MMGraphRAG: Bridging Vision and Language with Interpretable Multimodal Knowledge Graphs

Superseded baseline#52 of 1,179 most-superseded · first seen Jul 28, 2025

Superseded — cited as a baseline and beaten by newer methods

2 papers critique it · 2 beat it on benchmarks

What papers say

Verbatim critique sentences, each from a paper that cites MMGraphRAG as a baseline.

such approaches typically convert visual content into textual graph nodes via MLLMs, effectively reducing multimodal structure to text-centric representations. As a result, fine-grained visual evidence may be abstracted away, limiting faithful cross-modal reasoning.

— MG$^2$-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation

“MMGraphRAG links scene graphs with textual representations but suffers from structural blindness—treating tables and formulas as plain text without proper entity extraction, losing structural information for reasoning”

— RAG-Anything: All-in-One RAG Framework

Beaten on benchmarks

Head-to-head results where a newer method reports beating MMGraphRAG. Values are copied from the source paper's tables — verify against the cited paper.

MG²-RAG beats MMGraphRAG
38.15 vs 0.39
InfoSeek Unseen-E · [Qwen2.5-VL-7B backbone]
MG$^2$-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation
RAGAnything beats MMGraphRAG
42.8 vs 37.7
Accuracy · [Overall]
RAG-Anything: All-in-One RAG Framework

What to use instead

Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.