# CrossScope: A Role-Asymmetric World Model for Joint Dual-Scope Surgical Video Prediction

arXiv: https://arxiv.org/abs/2608.03211 · HTML: https://mlsanity.com/paper/2608.03211/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Medical and surgical world models, one of 11 directions in World models.
- Builds on 13 of its 29 references that are in the map.
- First posted on arXiv 4 Aug 2026.

## Placed in

- World models / [Medical and surgical world models](https://mlsanity.com/wm/medical-and-surgical-world-models/)

## Builds on (most cited first, 13 of 13)

- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Flow Matching for Generative Modeling](https://mlsanity.com/paper/2210.02747/) (2022)
- [HunyuanVideo: A Systematic Framework For Large Video Generative Models](https://mlsanity.com/paper/2412.03603/) (2024)
- [World Models](https://mlsanity.com/paper/1803.10122/) (2018)
- [GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium](https://mlsanity.com/paper/1706.08500/) (2017)
- [VISAGE: Video Synthesis using Action Graphs for Surgery](https://mlsanity.com/paper/2410.17751/) (2024)
- [Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling](https://mlsanity.com/paper/2512.23162/) (2025)
- [SAW: Toward a Surgical Action World Model via Controllable and Scalable Video Generation](https://mlsanity.com/paper/2603.13024/) (2026)
- [SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos](https://mlsanity.com/paper/2602.05638/) (2026)
- [From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation](https://mlsanity.com/paper/2605.08712/) (2026)
- [Scaling Video Pretraining for Surgical Foundation Models](https://mlsanity.com/paper/2603.29966/) (2026)
- [SurgVista: Long-Horizon Surgical World Modeling with Plausible Instrument-Tissue Dynamics](https://mlsanity.com/paper/2606.19889/) (2026)

## Abstract (arXiv)

Visual world models typically learn future dynamics from a single observation stream, limiting their ability to model cooperative systems with multiple independently moving observers. We investigate this challenge in Mother--Child endoscopic retrograde cholangiopancreatography (ERCP), where two flexible scopes provide complementary yet role-dependent views without a calibrated stereo relationship. Unlike conventional multi-view fusion that assumes symmetric information exchange, we formulate role-asymmetric dual-scope future prediction, where cross-view evidence is selectively transferred according to the prediction target and its underlying spatial requirements. We propose CrossScope, a dual-stream surgical world model that preserves view-specific experts while enabling target-specific evidence routing through geometry-guided residual interactions. CrossScope learns two complementary communication directions: geometric motion cues from the Mother view guide Child-view future dynamics, while pose-aligned Child appearance supports Mother-view prediction only when valid spatial correspondence is established. This design allows each scope to contribute task-relevant evidence without compromising its view-specific representation. To evaluate this problem, we establish a paired dual-scope benchmark comprising synchronized phantom and real-world ERCP episodes, with evaluations assessing visual fidelity, structural preservation, target localization, and motion consistency. Experiments demonstrate that CrossScope consistently outperforms strong surgical video generation baselines, validating the importance of role-aware evidence routing for multi-observer visual world modeling.