Add pipeline tag and improve documentation

README.md

@@ -1,22 +1,24 @@
 ---
+base_model:
+- openai/clip-vit-base-patch32
+- openai/clip-vit-base-patch16
+- openai/clip-vit-large-patch14
 license: mit
+pipeline_tag: image-classification
 tags:
-  - clip
-  - task-arithmetic
-  - model-merging
-  - fine-tuning
-  - orthogonal-regularization
-  - image-classification
-base_model:
-  - openai/clip-vit-base-patch32
-  - openai/clip-vit-base-patch16
-  - openai/clip-vit-large-patch14
+- clip
+- task-arithmetic
+- model-merging
+- fine-tuning
+- orthogonal-regularization
 ---
 
 # Understanding and Enforcing Weight Disentanglement in Task Arithmetic
 
 [CVPR 2026] Official checkpoints for the paper **"Understanding and Enforcing Weight Disentanglement in Task Arithmetic"**.
 
+**Authors**: [Shangge Liu](https://huggingface.co/gezi2333), Yuehan Yin, Lei Wang, Qi Fan, Yinghuan Shi, Wenbin Li, Yang Gao, and Dacheng Tao.
+
 [[Paper](https://arxiv.org/abs/2604.17078)]   [[Code](https://github.com/RL-MIND/OrthoReg)]
 
 ---
@@ -145,15 +147,6 @@ python src/eval_task_negation.py \
 
 > Run `eval_single_task` with `--finetuning-mode none --ortho-lambda 0` first to generate `zeroshot_accuracies.json`, which is required as the reference for normalized accuracy.
 
-### Argument reference
-
-| Argument | Value for these checkpoints |
-|---|---|
-| `--seed` | `1993` |
-| `--lr` | `1e-5` |
-| `--ortho-lambda` | `0` for baselines, `xx` for OrthoReg variants |
-| `--finetuning-mode` | see table above |
-
 ---
 
 ## 📦 Datasets
@@ -182,4 +175,4 @@ If you find this work useful, please cite:
 
 ## 📬 Acknowledgements
 
-This codebase is built on top of [Task Arithmetic](https://github.com/mlfoundations/task_vectors), [Tangent Task Arithmetic](https://github.com/gortizji/tangent_task_arithmetic), and [Attention-Only Fine-tuning](https://github.com/kyrie-23/linear_task_arithmetic). We thank the authors for releasing their code.
+This codebase is built on top of [Task Arithmetic](https://github.com/mlfoundations/task_vectors), [Tangent Task Arithmetic](https://github.com/gortizji/tangent_task_arithmetic), and [Attention-Only Fine-tuning](https://github.com/kyrie-23/linear_task_arithmetic). We thank the authors for releasing their code.