Paper Detail

AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilities

Yuqing Wen, Yukai Huang, Qianqian Xie, Jiangtao Wu, Yibin Lin, Yikai Gu, Jialu Chen, Yuanxing Zhang, Jiaheng Liu

huggingface Score 11.0

Published 2026-07-17 · First seen 2026-08-06

General AI

Abstract

While instruction-based video editing has advanced rapidly, real-world videos contain tightly coupled audio and visual signals, and editing one modality often requires coordinated changes in the other. Existing benchmarks primarily evaluate visual transformations on silent clips or isolated audio editing, leaving complex audio-visual editing and cross-modal consistency underexplored. We introduce AVE-Compass, a comprehensive benchmark with 145 curated source videos, 196 audio-visually coupled editing instructions, and 2,688 fine-grained checklist items. It evaluates Instruction Following, Fidelity Preserving, Realism, and Editing Intent through checklist-based MLLM judging and a dedicated realism rubric, complemented by automated cross-modal, video, and audio metrics. Extensive evaluation shows that state-of-the-art models still struggle to execute cross-modal instructions while preserving non-target content. We further propose AVE-Agent, a modular agent framework that decomposes complex instructions into dependent subtasks and iteratively improves editing results through self-reflection and evaluator feedback. AVE-Agent improves instruction execution, Fidelity Preserving, and audio-visual alignment in joint editing while maintaining competitive perceptual quality.

Workflow Status

Review status
pending
Role
unreviewed
Read priority
soon
Vote
Not set.
Saved
no
Collections
Not filed yet.
Next action
Not filled yet.

Reading Brief

No structured notes yet. Add `summary_sections`, `why_relevant`, `claim_impact`, or `next_action` in `papers.jsonl` to enrich this view.

Why It Surfaced

No ranking explanation is available yet.

Tags

No tags.

BibTeX

@misc{wen2026ave,
  title = {AVE-Compass: Towards Holistic Evaluation for Audio-Video Editing Abilities},
  author = {Yuqing Wen and Yukai Huang and Qianqian Xie and Jiangtao Wu and Yibin Lin and Yikai Gu and Jialu Chen and Yuanxing Zhang and Jiaheng Liu},
  year = {2026},
  abstract = {While instruction-based video editing has advanced rapidly, real-world videos contain tightly coupled audio and visual signals, and editing one modality often requires coordinated changes in the other. Existing benchmarks primarily evaluate visual transformations on silent clips or isolated audio editing, leaving complex audio-visual editing and cross-modal consistency underexplored. We introduce AVE-Compass, a comprehensive benchmark with 145 curated source videos, 196 audio-visually coupled ed},
  url = {https://huggingface.co/papers/2607.24821},
  keywords = {code available, huggingface daily},
  eprint = {2607.24821},
  archiveprefix = {arXiv},
}

Metadata

{}