VLM baseline
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3d7eaca9-6504-44dd-ba9b-ec53c2b1c607 — Aug. 8, 2026
Summary
A Qwen3.5-4B VLM directly takes the QA and frames and returns its answer.
Mechanism
The model was finetuned (LoRA) on all available data (train/test splits of both heico and laphchole). For inference, parameters used are temperature 0, top-p 1, top-k -1, maximum 128 new tokens.
Interfaces
This algorithm implements all of the following input-output combinations:
Validation and Performance
When trained on the train set only, these are the results on the testset, from the official evaluator:
| Accuracy | |
|---|---|
| Heico | 0.7154 |
| Lapchole | 0.6207 |
Challenge Performance
| Date | Challenge | Phase | Rank |
|---|---|---|---|
| Aug. 8, 2026 | FRAME | FRAME Track - Pre-evaluation phase | 51 |
Uses and Directions
This algorithm was developed for research purposes only.
Warnings
Left empty by the Algorithm Editors
Common Error Messages
Left empty by the Algorithm Editors
Information on this algorithm has been provided by the Algorithm Editors,
following the Model Facts labels guidelines from
Sendak, M.P., Gao, M., Brajer, N. et al.
Presenting machine learning model information to clinical end users with model facts labels.
npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3