mlsanityData to 14 Oct 2026

ReactiveGWM: Steering NPC in Reactive Game World Models

arXiv 2605.15256 ↗First posted 14 May 2026cs.CVcited by 9

On the map: World models → Video-generation world models and simulators

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.

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.

Builds on

9 of 19 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory10 Apr
  2. 2026ActionParty: Multi-Subject Action Binding in Generative Video Games2 Apr
  3. 2026Solaris: Building a Multiplayer Video World Model in Minecraft25 Feb
  4. 2025Wan: Open and Advanced Large-Scale Video Generative Models26 Mar
  5. 2025GameFactory: Creating New Games with Generative Interactive Videos14 Jan
  6. 2024Diffusion Models Are Real-Time Game Engines27 Aug

Other references · 3

  1. 2018World Modelscited by 1,513
  2. 2024Diffusion for World Modeling: Visual Details Matter in Ataricited by 300
  3. 2023UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretrainingcited by 151

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 9.

9 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026GameWAM: A World Action Model for Video Games
  2. 2026NitroGen: An Open Foundation Model for Generalist Gaming Agents
  3. 2025Hunyuan-GameCraft-2: Instruction-following Interactive Game World Model
  4. 2026Player-1: Learning to Play from Synthetic Experience
  5. 2026Mind-Studio: Executable World Models with Lookahead Evaluation for Partially Observable Games
  6. 2026Multiplayer Interactive World Models with Representation Autoencoders
  7. 2026COMBAT: Conditional World Models for Behavioral Agent Training
  8. 2026MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines