
WorldMark: A Unified Benchmark Suite for Interactive Video World Models
From Daily Paper Cast by Jingwen Liang, Gengyu Wang
April 25, 2026 · 26 min · Episode 1802
About this episode
The episode discusses WorldMark, a benchmark suite designed for fair evaluation of interactive video generation models.
🤗 Upvotes: 30 | cs.CV Authors: Xiaojie Xu, Zhengyuan Lin, Kang He, Yukang Feng, Xiaofeng Mao, Yuanyang Yin, Kaipeng Zhang, Yongtao Ge Title: WorldMark: A Unified Benchmark Suite for Interactive Video World Models Arxiv: http://arxiv.org/abs/2604.21686v1 Abstract: Interactive video generation models such as Genie, YUME, HY-World, and Matrix-Game are advancing rapidly, yet every model is evaluated on its own benchmark with private scenes and trajectories, making fair cross-model comparison impossible. Existing public benchmarks offer useful metrics such as trajectory error, aesthetic scores, and VLM-based judgments, but none supplies the standardized test conditions -- identical scenes, identical action sequences, and a unified control interface -- needed to make those metrics comparable across models with heterogeneous inputs. We introduce WorldMark, the first benchmark that provides such a common playing field for interactive Image-to-Video world models. WorldMark contributes: (1) a unified action-mapping layer that translates a shared WASD-style action vocabulary into each model's native control format, enabling apples-to-apples comparison across six major models on identical…
People in this episode
Hosts: Jingwen Liang, Gengyu Wang
Topics covered
- interactive video generation
- benchmarking
- model comparison
- video world models
- evaluation metrics
Keywords
- WorldMark
- benchmark suite
- interactive video
- model evaluation
- video generation
Mentioned in this episode
Organizations: Genie, YUME, HY-World, Matrix-Game
Books & works: WorldMark: A Unified Benchmark Suite for Interactive Video World Models
More episodes of Daily Paper Cast
- EvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic Environments · June 13, 2026 · 24 min
- MiniMax Sparse Attention · June 13, 2026 · 26 min
- SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning · June 13, 2026 · 23 min
- InterleaveThinker: Reinforcing Agentic Interleaved Generation · June 13, 2026 · 21 min
- FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents · June 13, 2026 · 23 min
- Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding? · June 13, 2026 · 20 min
Explore listener stats, chart rankings, contacts and more on the Daily Paper Cast podcast page.