--- license: mit base_model: llava-hf/llava-1.5-7b-hf library_name: peft tags: - vision-language - lora - accv-2026 - gate-closure - llava-1.5-7b --- # LoRA on all linear layers (seed 1, 1 epoch) (lora_all_linear_r1) Checkpoint **`lora_all_linear_r1`** from *The Gate Always Closes: On Injecting Auxiliary Signals into Frozen Vision-Language Models* (ACCV 2026, [arXiv:2607.23335](https://arxiv.org/abs/2607.23335)). Paper label: **LoRA on all linear layers (seed 1, 1 epoch)**. Code and the reproduction scripts: . ## What this is Prefix design: K=4 tokens from the hyperbolic relational graph are spliced after the image patches; `variant.json` says whether the prefix is RMS-normalised and whether it is gated. | field | value | |---|---| | kind | `prefix` | | variant (`VARIANT_CONFIGS` key) | `lora_all_linear` | | backbone | `llava-hf/llava-1.5-7b-hf` (not redistributed; downloaded from its own repo) | | learned gate | gate_raw = 0.0235, gate_tanh = 0.0235 | | trainer | `see variant.json` | | files | lora, prefix_modules.pt, variant.json | `variant.json` records the configuration the graph module must be rebuilt with; the release code reads it (`hra.checkpoints`). The `lora/` adapter is a standard PEFT adapter for the base model. ## Load ```python from hra import hub from hra.checkpoints import load_for_eval model, processor, wrapper = load_for_eval("prefix", "lora_all_linear_r1", "cuda") # downloads this repo ``` ## Behavioural knock-out (from the paper's result files) | benchmark | pathway off | pathway on (learned) | delta [95% CI] | |---|---|---|---| | GQA-rel (n=1,000) (n=1000) | 54.5 | 54.2 | -0.3 [-0.9, +0.3] | | SugarCrepe (n=1,000) (n=1000) | 80.6 | 79.8 | -0.8 [-1.4, -0.3] | ## Licence and citation Code and these adapter weights: MIT. The base model's own licence applies to the base weights (llava-hf/llava-1.5-7b-hf). Please cite the paper: ```bibtex @InProceedings{Farazi_2026_ACCV, author = {Farazi, Moshiur and Ramasinghe, Sameera and Ciftler, Bekir Sait and Turza, Mahbub Ahmed and Rahman, Shafin}, title = {The Gate Always Closes: On Injecting Auxiliary Signals into Frozen Vision-Language Models}, booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)}, month = {December}, year = {2026} } ```