ReactiveGWM-Datasets is the strategy-aligned training corpus that powers ReactiveGWM, a game world model that decouples player control from NPC autonomy. To learn that decoupling, the model needs supervision that pairs each gameplay clip with both a per-frame action stream (what the player did) and a high-level NPC description (what the NPC tried to do, and under which strategy).
This dataset provides exactly that, on two classic Capcom fighting games:
| Subset | Game (platform) | Clips | Length |
|---|---|---|---|
SF2 | Street Fighter II: Champion Edition (Sega Genesis) | 10,000 | 5 s |
SF3 | Street Fighter III: New Generation / 3rd Strike (CPS3) | 10,000 | 5 s |
Each clip comes with two parallel annotations: a structured prompt that
exposes NPC Active_Behavior, Passive_Behavior, and one of three strategy
classes (Offense / Control / Defense) β used to train ReactiveGWM's
cross-attention NPC modules β and a free-form vanilla narration prompt
suitable for vanilla game model baselines.
SF2/
βββ clips/
β βββ clip_0000000/
β β βββ video.mp4 # 5-second gameplay clip
β β βββ actions.parquet # per-frame controller inputs for both players
β βββ ...
βββ metadata.csv # video, action, structured NPC behavior + strategy
βββ metadata_vanilla.csv # video, action, natural-language narration
SF3/ (same layout)
metadata.csv β structured strategy promptEach row is video, action, prompt. The prompt column tags the NPC's
moves and ends with one of the three strategy classes that ReactiveGWM's
cross-attention modules condition on:
NPC: Active_Behavior(<move>: <desc>; ...),
Passive_Behavior(<move>: <desc>; ...),
Strategy(Offense | Control | Defense : <desc>)
Example (SF2):
NPC: Active_Behavior(Walk Right: Moves character towards the right side of the screen.), Passive_Behavior(Standing Block: Passively guards against high or mid attacks while standing.; Take Damage: ...; Knockback: ...; Knockdown: ...; Wake Up: ...), Strategy(Defense: Absorbs and evades incoming pressure, recovering safely instead of trading hits.)
metadata_vanilla.csv β natural-language promptSame video, action pairs but with free-form English narration, suitable
for prompting vanilla text-to-video baselines:
"Street Fighter 2, At the Air Force Base, Ryu on the left crouches and then throws a standing punch that hits Guile on the right, after which Ryu walks right and throws another standing punch as Guile walks left and throws his own standing punch."
actions.parquetPer-frame discrete controller state for both players (buttons + d-pad), aligned 1-to-1 with the video frames. This is the signal injected as a lightweight additive bias into the diffusion backbone in ReactiveGWM.
Rollouts are produced by a random agent fighting the built-in arcade AI,
recorded through stable-retro
(SF3 runs on a CPS-3 integration). The full pipeline β record β split into
5-second clips β multi-stage labelling (initial β class-balance β final
fact-check β hard-rule strategy classification) β optional visual labelling
β lives in a separate code release and is not distributed in this
repository.
Annotations in the prompt columns are produced by an LLM
(Gemini) over the recorded
clips and then filtered with hard rules. They are machine-generated and
may contain residual noise.
Gameplay recording uses the stable-retro framework (SF3 via a CPS-3 custom integration on top of FBNeo). NPC strategy annotations are produced by Gemini. The Street Fighter games themselves are Β© Capcom Co., Ltd.; see the IP notice below. We thank the open-source community for their valuable contributions.
If you use this dataset, please cite:
@misc{wang2026reactivegwmsteeringnpcreactive,
title={ReactiveGWM: Steering NPC in Reactive Game World Models},
author={Zeqing Wang and Danze Chen and Zhaohu Xing and Zizhao Tong and Yinhan Zhang and Xingyi Yang and Yeying Jin},
year={2026},
eprint={2605.15256},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.15256},
}
Read this before using the dataset.
This dataset contains derivative material from two commercial video games whose copyright the dataset authors do not own:
All in-game visuals, character designs, sprites, backgrounds, audio, and
game mechanics depicted in the .mp4 clips remain the exclusive
property of Capcom Co., Ltd. No ownership over the underlying games is
claimed or transferred by this release.
The CC BY-NC 4.0 license declared in the YAML header applies only to the contributions that are original to this dataset:
metadata.csv and metadata_vanilla.csv
(the prompt column),actions.parquet action traces produced by the recording
scripts.The video frames and audio inside clips/*/video.mp4 are made
available solely under fair-use / fair-dealing for non-commercial
academic research on game AI, world models, and video understanding.
They are not relicensed, and CC BY-NC 4.0 does not grant you any
right to the underlying Capcom IP. See the LICENSE and NOTICE files
shipped alongside this README for the full statement.
No game ROMs are included in this repository, and none will be provided. Reproducing the dataset from the upstream generation code requires you to obtain legal copies of the original Street Fighter II (Genesis) and Street Fighter III (CPS3) ROMs yourself, in accordance with the laws of your jurisdiction.
If you are a rights holder (in particular Capcom Co., Ltd. or an authorised representative) and believe this dataset infringes your rights, please contact zeqing.wang@u.nus.edu with a description of the material in question. The maintainer will respond and, where appropriate, remove the contested content promptly.
ReactiveGWM-Datasets is the strategy-aligned training corpus that powers ReactiveGWM, a game world model that decouples player control from NPC autonomy. To learn that decoupling, the model needs supervision that pairs each gameplay clip with both a per-frame action stream (what the player did) and a high-level NPC description (what the NPC tried to do, and under which strategy).
This dataset provides exactly that, on two classic Capcom fighting games:
| Subset | Game (platform) | Clips | Length |
|---|---|---|---|
SF2 | Street Fighter II: Champion Edition (Sega Genesis) | 10,000 | 5 s |
SF3 | Street Fighter III: New Generation / 3rd Strike (CPS3) | 10,000 | 5 s |
Each clip comes with two parallel annotations: a structured prompt that
exposes NPC Active_Behavior, Passive_Behavior, and one of three strategy
classes (Offense / Control / Defense) β used to train ReactiveGWM's
cross-attention NPC modules β and a free-form vanilla narration prompt
suitable for vanilla game model baselines.
SF2/
βββ clips/
β βββ clip_0000000/
β β βββ video.mp4 # 5-second gameplay clip
β β βββ actions.parquet # per-frame controller inputs for both players
β βββ ...
βββ metadata.csv # video, action, structured NPC behavior + strategy
βββ metadata_vanilla.csv # video, action, natural-language narration
SF3/ (same layout)
metadata.csv β structured strategy promptEach row is video, action, prompt. The prompt column tags the NPC's
moves and ends with one of the three strategy classes that ReactiveGWM's
cross-attention modules condition on:
NPC: Active_Behavior(<move>: <desc>; ...),
Passive_Behavior(<move>: <desc>; ...),
Strategy(Offense | Control | Defense : <desc>)
Example (SF2):
NPC: Active_Behavior(Walk Right: Moves character towards the right side of the screen.), Passive_Behavior(Standing Block: Passively guards against high or mid attacks while standing.; Take Damage: ...; Knockback: ...; Knockdown: ...; Wake Up: ...), Strategy(Defense: Absorbs and evades incoming pressure, recovering safely instead of trading hits.)
metadata_vanilla.csv β natural-language promptSame video, action pairs but with free-form English narration, suitable
for prompting vanilla text-to-video baselines:
"Street Fighter 2, At the Air Force Base, Ryu on the left crouches and then throws a standing punch that hits Guile on the right, after which Ryu walks right and throws another standing punch as Guile walks left and throws his own standing punch."
actions.parquetPer-frame discrete controller state for both players (buttons + d-pad), aligned 1-to-1 with the video frames. This is the signal injected as a lightweight additive bias into the diffusion backbone in ReactiveGWM.
Rollouts are produced by a random agent fighting the built-in arcade AI,
recorded through stable-retro
(SF3 runs on a CPS-3 integration). The full pipeline β record β split into
5-second clips β multi-stage labelling (initial β class-balance β final
fact-check β hard-rule strategy classification) β optional visual labelling
β lives in a separate code release and is not distributed in this
repository.
Annotations in the prompt columns are produced by an LLM
(Gemini) over the recorded
clips and then filtered with hard rules. They are machine-generated and
may contain residual noise.
Gameplay recording uses the stable-retro framework (SF3 via a CPS-3 custom integration on top of FBNeo). NPC strategy annotations are produced by Gemini. The Street Fighter games themselves are Β© Capcom Co., Ltd.; see the IP notice below. We thank the open-source community for their valuable contributions.
If you use this dataset, please cite:
@misc{wang2026reactivegwmsteeringnpcreactive,
title={ReactiveGWM: Steering NPC in Reactive Game World Models},
author={Zeqing Wang and Danze Chen and Zhaohu Xing and Zizhao Tong and Yinhan Zhang and Xingyi Yang and Yeying Jin},
year={2026},
eprint={2605.15256},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.15256},
}
Read this before using the dataset.
This dataset contains derivative material from two commercial video games whose copyright the dataset authors do not own:
All in-game visuals, character designs, sprites, backgrounds, audio, and
game mechanics depicted in the .mp4 clips remain the exclusive
property of Capcom Co., Ltd. No ownership over the underlying games is
claimed or transferred by this release.
The CC BY-NC 4.0 license declared in the YAML header applies only to the contributions that are original to this dataset:
metadata.csv and metadata_vanilla.csv
(the prompt column),actions.parquet action traces produced by the recording
scripts.The video frames and audio inside clips/*/video.mp4 are made
available solely under fair-use / fair-dealing for non-commercial
academic research on game AI, world models, and video understanding.
They are not relicensed, and CC BY-NC 4.0 does not grant you any
right to the underlying Capcom IP. See the LICENSE and NOTICE files
shipped alongside this README for the full statement.
No game ROMs are included in this repository, and none will be provided. Reproducing the dataset from the upstream generation code requires you to obtain legal copies of the original Street Fighter II (Genesis) and Street Fighter III (CPS3) ROMs yourself, in accordance with the laws of your jurisdiction.
If you are a rights holder (in particular Capcom Co., Ltd. or an authorised representative) and believe this dataset infringes your rights, please contact zeqing.wang@u.nus.edu with a description of the material in question. The maintainer will respond and, where appropriate, remove the contested content promptly.