# ReactiveGWM: Steering NPC in Reactive Game World Models

arXiv: https://arxiv.org/abs/2605.15256 · HTML: https://mlsanity.com/paper/2605.15256/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Placed in Video-generation world models and simulators, one of 11 directions in World models.
- Builds on 9 of its 19 references that are in the map.
- First posted on arXiv 14 May 2026.

## Placed in

- World models / [Video-generation world models and simulators](https://mlsanity.com/wm/video-generation-world-models-and-simulators/)

## Builds on (most cited first, 9 of 9)

- [Wan: Open and Advanced Large-Scale Video Generative Models](https://mlsanity.com/paper/2503.20314/) (2025)
- [World Models](https://mlsanity.com/paper/1803.10122/) (2018)
- [Diffusion for World Modeling: Visual Details Matter in Atari](https://mlsanity.com/paper/2405.12399/) (2024)
- [Diffusion Models Are Real-Time Game Engines](https://mlsanity.com/paper/2408.14837/) (2024)
- [UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining](https://mlsanity.com/paper/2304.09151/) (2023)
- [GameFactory: Creating New Games with Generative Interactive Videos](https://mlsanity.com/paper/2501.08325/) (2025)
- [Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory](https://mlsanity.com/paper/2604.08995/) (2026)
- [Solaris: Building a Multiplayer Video World Model in Minecraft](https://mlsanity.com/paper/2602.22208/) (2026)
- [ActionParty: Multi-Subject Action Binding in Generative Video Games](https://mlsanity.com/paper/2604.02330/) (2026)

## Built on by (most cited first, 9 of 9)

- [StatePlay: State-Aware Game World Models for Mechanics-Consistent Generation](https://mlsanity.com/paper/2607.26754/) (2026)
- [Marionette: Predicting World States, Rendering Geometry, Painting Appearance](https://mlsanity.com/paper/2608.14530/) (2026)
- [From Pixels to States: Rethinking Interactive World Models as Game Engines](https://mlsanity.com/paper/2607.14076/) (2026)
- [H3-World: Turning Language Understanding into World Control](https://mlsanity.com/paper/2609.01560/) (2026)
- [WorldMind: Decoupled Game World Model for State-Aware NPC Behavior](https://mlsanity.com/paper/2608.21439/) (2026)
- [AI for Games in the Foundation Model Era](https://mlsanity.com/paper/2609.16679/) (2026)
- [HelloWorld: Enabling Socially Interactive Characters in Video World Models](https://mlsanity.com/paper/2608.05070/) (2026)
- [GameDirector: Decoupling Gameplay Logic from Rendering for Player-Configurable Game World Models](https://mlsanity.com/paper/2609.25652/) (2026)
- [LongLive-Plug: Once-for-All Distillation for Video Generation](https://mlsanity.com/paper/2609.38154/) (2026)

## Abstract (arXiv)

Existing game world models typically adopt role-specific interactions, where player and NPC roles are bound to fixed characters. This limits their flexibility in multi-character games, where different characters may receive external control while NPCs must react to interactions triggered by players. This setting raises two key challenges: how to flexibly assign control roles to individual characters, and how to support direct player control and reactive NPC behavior within a unified model. These challenges are particularly pronounced in shared-view 2D games, where multiple, potentially visually identical characters share the same viewpoint, making camera cues insufficient to distinguish their roles. To address these challenges, we introduce ReactiveGWM, a reactive game world model that flexibly assigns control modes at initialization and jointly simulates externally controlled players and reactive NPCs. Specifically, ReactiveGWM introduces Spatial Role Binding, which grounds learned character handles to their corresponding regions in the initial frame using instance masks. Building on these handles, Unified Agency Conditioning unifies heterogeneous control signals across characters by encoding player actions and conditional NPC rules into character-specific control-token groups. Each group is then bound to its corresponding character handle, enabling the model to apply each control signal to its designated character. Meanwhile, causal self-attention restricts temporal context to the current and preceding latent frames when generating player actions and NPC responses. Experiments on two multi-character 2D games demonstrate that ReactiveGWM supports flexible character control across different player/NPC role assignments while jointly generating accurate player-controlled behaviors and reactive NPC responses, enabling more configurable and richer multi-character interactions.