arXiv Computation and Language September 18, 2026 By Tithi Rakshit, Hongkuan Zhou, Lavdim Halilaj, Yuqicheng Zhu

Less Is More: Graph-free Multimodal RAG via Multi-signal Late Fusion

Read the original on arXiv Computation and Language →

The paper introduces TrioRAG, a graph-free multimodal retrieval-augmented generation framework that combines evidence from the question, an anchor image, and a VLM-enhanced query via late fusion. It also presents AutoQA, a benchmark featuring noisy web-sourced images that require reasoning across manuals. TrioRAG outperforms graph-based systems on three benchmarks while cutting costs and speeding up inference by 1.6–2.3×.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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