UCIT continual instruction tuning β€” probes β€” LLaVA-1.5-7B

LoRA adapters trained sequentially on the 6-task UCIT benchmark, in this order:

ImageNet-R β†’ ArxivQA β†’ VizWiz-Caption β†’ IconQA β†’ CLEVR-Math β†’ Flickr30k

Each <run>/Task<N>_<Name>/ holds the adapter after training task N, so the full 6x6 forward-transfer matrix evaluates checkpoint N on every task K<=N.

The CLIP vision tower is frozen in every run here; non_lora_trainables.bin carries the mm_projector only (21.0M parameters, no vision_tower.* keys).

Contents

run size tasks
ewc_lam1_ucit_llava 1.5G 3
ewc_lam5_ucit_llava 1.5G 3
ewc_lam1e5_ucit_llava 1.5G 3
ewc_ucit_llava_zero_fisher 2.5G 5
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