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.

翻译：视听生成正从短片段快速迈向分钟级长内容，然而现有评估体系仍主要局限于短时场景。当前基准测试多聚焦于5-10秒的文本条件生成，鲜少支持文本、图像与视频条件模式的统一评估。此外，它们在身份一致性、叙事连贯性及视听对齐性随时间退化方面的分析能力极为有限。为填补这一空白，我们提出LongAV-Compass——一个面向分钟级视听生成的系统性基准。LongAV-Compass包含284个精心设计的测试案例，涵盖文本到音频-视频（T2AV）、图像到音频-视频（I2AV）及视频到音频-视频（V2AV）三类任务，并按应用场景与生成复杂度进行组织。该基准结合了分类学引导的构建方法与统一评估框架，整合了MLLM辅助评估与互补性感知及多模态指标（包括DINO-v2、ArcFace、CLIP和ImageBind）。该框架评估超过20个细粒度维度，覆盖片段内质量、跨片段一致性、全局叙事连贯性、语义对齐及视听同步性。通过对11个代表性模型的实验及人工对齐验证，LongAV-Compass为分析当前系统在不同输入模态下维持连贯、语义对齐及时间一致的分钟级视听生成能力的局限性，提供了诊断性测试平台。