| --- |
| base_model: meta-llama/Llama-2-7b-chat-hf |
| library_name: peft |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - audio |
| - video |
| - segmentation |
| - mask-quality-assessment |
| - audio-visual-segmentation |
| - lora |
| --- |
| |
| # MQ-Auditor HyperLoRA Weights |
|
|
| This repository contains the released MQ-Auditor pretrained weights for reference-free mask quality assessment in language-referred audio-visual segmentation. |
|
|
| The checkpoint corresponds to: |
|
|
| ```text |
| epochs96_lr1e-4_bs4_gradacc8_lora_r32alpha64_pos0.5_ioulosswei0 |
| ``` |
|
|
| ## Model |
|
|
| MQ-Auditor takes a video clip, audio, a referring expression, a frame, and a candidate segmentation mask, then predicts mask quality attributes such as mask type, IoU, and recommended action. |
|
|
| The released weights are intended to be used with the MQ-Auditor codebase and MQ-RAVSBench dataset. The base LLM checkpoint and external encoders are not included in this package. |
|
|
| ## Release Contents |
|
|
| The public weight package should include: |
|
|
| ```text |
| adapter_config.json |
| adapter_model.safetensors |
| config.json |
| model.txt |
| model_trainable_params.txt |
| non_lora_trainables.bin |
| saved_config.json |
| trainer_state.json |
| checkpoint-960/ |
| config.json |
| finetune_weights.bin |
| ``` |
|
|
| Intermediate epoch checkpoints and TensorBoard logs are not part of the release package. |
|
|
| ## Training Data |
|
|
| The model was trained on MQ-RAVSBench with: |
|
|
| ```text |
| train_test_meta_files/metadata.csv |
| train_test_meta_files/train_audit_only_filtered.json |
| ``` |
|
|
| `null` masks are used during training as empty-mask examples. They are not part of the default/reported test-time evaluation protocol. |
|
|
| ## Evaluation |
|
|
| Evaluation is reported on the seen and unseen MQ-RAVSBench test splits: |
|
|
| ```text |
| test_s_image_filtered.json |
| test_u_image_filtered.json |
| test_s_video_filtered.json |
| test_u_video_filtered.json |
| ``` |
|
|
| Reported mask types focus on non-empty candidate masks: `perfect`, `cutout`, `erode`, `dilate`, `merge`, and `full_neg`. |
|
|
| ## License |
|
|
| The released MQ-Auditor weights are provided for non-commercial research purposes only under CC BY-NC-SA 4.0-style terms. The weights depend on the Llama-2 base model and other pretrained encoders, so users must also comply with the applicable upstream model licenses and access terms. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{zhou2026audit, |
| title={Audit After Segmentation: Reference-Free Mask Quality Assessment for Language-Referred Audio-Visual Segmentation}, |
| author={Zhou, Jinxing and Zhou, Yanghao and Wang, Yaoting and Han, Zongyan and Ma, Jiaqi and Ding, Henghui and Anwer, Rao Muhammad and Cholakkal, Hisham}, |
| journal={arXiv preprint arXiv:2602.03892}, |
| year={2026} |
| } |
| ``` |
|
|
| Paper: https://arxiv.org/pdf/2602.03892 |
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|
