route-images-expert-backbones-prompted-mllm TEC-0309 · proposedRoute images to expert backbones with a prompted MLLM
An MLLM is prompted with the image plus blur/brightness/contrast/noise statistics and outputs one of five domain labels, dispatching the image to the matching fine-tuned vision expert, with an UNSURE option falling back to the best balanced
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
An MLLM is prompted with the image plus blur/brightness/contrast/noise statistics and outputs one of five domain labels, dispatching the image to the matching fine-tuned vision expert, with an UNSURE option falling back to the best balanced Filed by the drafting stage from MLLM-Routed Heterogeneous Ensembles for Robust Cross-Dataset Image Classification (2608.13463) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Unified-dataset top-1 accuracy: ARMDIL 90.78% vs best single backbone (balanced DINOv3) 89.61%, majority vote 90.47%, trained NN-Router 91.18%, oracle router 91.04%; per-domain routing accuracy 78.2-99.8%.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
Code
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Sources
Whether a technique works is a claim. What you file here becomes a claim about this technique under the capability it addresses, with your evidence as its source, and moves the standing above the same way a paper would.