dmusingu / lapvqa-diffvqa-native

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Model's Last Updated: June 06 2026
visual-question-answering

Introduction of lapvqa-diffvqa-native

Model Details of lapvqa-diffvqa-native

LAPVQA — Differential VQA (Native / End-to-end)

Part of the LAPVQA collection .

Description

DiffVQA models trained end-to-end (encoder + head jointly). Each .pt file is a plain state dict of DiffVQAHead . MAE-ViT-L/16 is the primary encoder studied.

Results (test set, MAE-ViT-L/16)
BLEU-4 ROUGE-2 RadGraph-s BERTScore F1
0.472 0.573 0.288 0.938
File Encoder vis_dim
clip-vit-l14_best.pt CLIP ViT-L/14 1024
coca_best.pt CoCa 768
florence2_best.pt Florence-2 1024
mae-vit-l16_best.pt MAE ViT-L/16 1024
siglip_best.pt SigLIP 1152
Loading
import torch
from lapvqa.diffvqa.model import DiffVQAHead

ckpt = torch.load("mae-vit-l16_best.pt", map_location="cpu")
head = DiffVQAHead(vis_dim=1024)
head.load_state_dict(ckpt)
head.eval()

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Total runs: 0
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Updated:June 06 2026
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Total runs: 0
Run Growth: 0
Growth Rate: 0.00%
Updated:June 06 2026