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ground2x_default from a four-arm controlled SFT study for
Android GUI use. The language model was fully fine-tuned while the complete
Qwen3-VL visual tower, merger, and deep-stack mergers remained frozen. The
uploaded weights were verified byte-for-byte against the pinned base for every
model.visual* tensor, while at least one language-model tensor was verified
to have changed.Qwen/Qwen3-VL-8B-Instruct at commit 0c351dd01ed87e9c1b53cbc748cba10e6187ff3bluca0621/appgen-sft-ngc-v1, config ngc-f-qwen3-normalized, revision 769ea99dbc4ff190048ae0db37eb6310dba595e0grounding2x1879d231697554ca0960366e3db9f70a97180694b9638720c1158dd9f32e6c9bproven; SHA-256 67ff8adb0e78a617f3d0edcf196d4e4cc3239967a8c30619fc5afc14484ee8c05e-7, cosine schedule, 5% warmupdefault loss scale was used.checkpoint-125) is published in
this repository. The exact training system prompt is included as
appgen_system_prompt.txt; run_manifest.json records hashes and verification
evidence. Intermediate 25-step checkpoints remain local for controlled eval.