A 5B-parameter latent diffusion model generates real-time four-player Rocket League matches conditioned on all players' actions, staying stable far beyond its training horizon.
International Conference on Learning Representations (ICLR) , year =
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Non-monotonic sampling schedules never improve upon monotonic baselines in diffusion models, with performance gaps ranging from substantial to negligible depending on the denoiser.
CNeVA combines variational behavior latents with rectified-flow generators and soft eligibility to deliver controllable yet realistic traffic simulation on Waymo data.
IConFace performs unified reference-aware and no-reference blind face restoration by asymmetrically conditioning identity from references and structure from the degraded image.
citing papers explorer
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Multiplayer Interactive World Models with Representation Autoencoders
A 5B-parameter latent diffusion model generates real-time four-player Rocket League matches conditioned on all players' actions, staying stable far beyond its training horizon.
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Is Monotonic Sampling Necessary in Diffusion Models?
Non-monotonic sampling schedules never improve upon monotonic baselines in diffusion models, with performance gaps ranging from substantial to negligible depending on the denoiser.
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Controllable Sim Agents with Behavior Latents
CNeVA combines variational behavior latents with rectified-flow generators and soft eligibility to deliver controllable yet realistic traffic simulation on Waymo data.
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IConFace: Identity-Structure Asymmetric Conditioning for Unified Reference-Aware Face Restoration
IConFace performs unified reference-aware and no-reference blind face restoration by asymmetrically conditioning identity from references and structure from the degraded image.