LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
LongAV-Compass is a systematic benchmark for evaluating minute-long audio-visual generation across text, image, and video conditioning. It contains 284 test cases, integrates MLLM-assisted assessment with perceptual metrics, and evaluates over 20 dimensions.
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Key points
- Introduces LongAV-Compass, a benchmark for minute-scale audio-visual generation evaluation.
- Covers T2AV, I2AV, and V2AV with 284 test cases.
- Uses MLLM-assisted and multimodal metrics to assess coherence, alignment, and synchronization.
- Experiments on 11 models reveal limitations in sustaining long-form generation.
Why it matters
This matters because introduces LongAV-Compass, a benchmark for minute-scale audio-visual generation evaluation.
Technical impact
May affect model selection, inference cost, product capability, and evaluation benchmarks.
[2605.26244] LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
[Submitted on 25 May 2026]
Title:LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
View a PDF of the paper titled LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV, by Tengfei Liu and 19 other authors
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Abstract:Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing benchmarks primarily focus on 5--10 second text-conditioned generation and rarely support unified evaluation across text, image, and video conditioning modalities. Moreover, they provide limited insight into how identity consistency, narrative coherence, and audio-visual alignment degrade over extended temporal horizons. To bridge this gap, we introduce LongAV-Compass, a systematic benchmark for minute-long audio-visual generation. LongAV-Compass contains 284 curated test cases spanning text-to-audio-video (T2AV), image-to-audio-video (I2AV), and video-to-audio-video (V2AV), organized by application scenario and generation complexity. The benchmark combines taxonomy-guided benchmark construction with a unified evaluation framework that integrates MLLM-assisted assessment with complementary perceptual and multimodal metrics, including DINO-v2, ArcFace, CLIP, and ImageBind. The framework evaluates more than 20 fine-grained dimensions covering within-segment quality, cross-segment consistency, global narrative coherence, semantic alignment, and audio-visual synchronization. Through experiments on 11 representative models together with human-alignment validation, LongAV-Compass provides a diagnostic testbed for analyzing the limitations of current systems in sustaining coherent, semantically aligned, and temporally consistent minute-scale audio-visual generation across diverse input modalities.
Subjects:
Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM); Sound (cs.SD)
Cite as: arXiv:2605.26244 [cs.CV]
(or arXiv:2605.26244v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2605.26244
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Yang Shi [view email] [v1] Mon, 25 May 2026 18:12:09 UTC (7,515 KB)
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