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中文(ZH) 实测可灵4.0：让AI跳一段舞，怎样更接近理想效果？

AI video models tested for dance generation, revealing editing challenges

By PulseAugur Editorial · [1 sources] ·

A review of the latest AI video generation models, including GLM-5.1, DeepSeek V4-Pro, Kimi K2.6, Qwen 3.7-max, and Minimax M3, highlights the challenges in achieving ideal results. While AI can streamline production, users still face significant effort in selecting, editing, and iterating on generated content. The review details a specific test case aiming to produce a 15-second dance video with particular stylistic and action requirements, emphasizing the need for user control over the final output. AI

IMPACT AI video generation models still require significant user input for editing and refinement, despite advancements in streamlining production.

RANK_REASON The article reviews and compares multiple AI models for video generation, presenting findings from practical tests. [lever_c_demoted from research: ic=1 ai=1.0]

Read on 雷峰网 (Leiphone) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI video models tested for dance generation, revealing editing challenges

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10 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
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The article reviews and compares multiple AI models for video generation, presenting findings from practical tests. [lever_c_demoted from research: ic=1 ai=1.0]
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, model release
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High
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. 雷峰网 (Leiphone) TIER_1 中文(ZH) ·

    Actual Test of KeLing 4.0: Let AI Dance, How to Get Closer to the Ideal Effect?

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