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cucl2
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Model Details
Model Provider
cucl2
Model Tree
Qwen/Qwen3-Omni-30B-A3B-Captioner
Input Modalities
Output Modalities
Supported Functionality
| Model | Avg (en) | Avg (zh) |
|---|---|---|
| Qwen3-Omni-30B-A3B-Captioner (dynamic rubric, no fine-tuning) | 76.77 | 76.66 |
| Gemini-2.5-Pro (holistic) | 77.72 | 80.01 |
| AnyAudio-Judge-30B (this checkpoint) | 84.45 | 85.26 |
This release contains the SFT-only stage (matching the "+SFT" row of the ablation table). The +GRPO improvement reported in the paper can be reproduced by running GRPO on top of this checkpoint.
python
from anyaudio_judge import AnyAudioJudge, decompose_instruction caption = "A gentle, delicate female voice, with soft and smooth pitch, calm and restrained throughout."rubric = decompose_instruction(caption) judge = AnyAudioJudge.from_pretrained("cucl2/AnyAudio-Judge-30B")result = judge.judge("./demo.wav", rubric)print("alignment_score:", result.score)for item in result.items: print(item.question, "->", item.answer)Apache-2.0, inheriting the license of the base Qwen3-Omni-30B-A3B-Captioner model.
bibtex
@misc{anyaudiojudge2026, title = {AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following}, author = {Anonymous Authors}, year = {2026}, note = {Preprint, under submission}}@misc{anyaudiojudge2026, title = {AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following}, author = {Anonymous Authors}, year = {2026}, note = {Preprint, under submission}}