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Keli Liu

2 accepted papers

2026

Advancing End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-Training

ICLR 2026poster

Pixel-space generative models are often more difficult to train and generally underperform compared to their latent-space counterparts, leaving a persistent performance and efficiency gap. In this paper, we introduce a novel two-stage training framework that closes this gap for pixel-space diffusion…

Cited by 0SourceScholar
2026

EchoGen: Generating Visual Echoes in Any Scene via Feed-Forward Subject-Driven Auto-Regressive Model

ICLR 2026poster

Subject-driven generation is a critical task in creative AI; yet current state-of-the-art methods present a stark trade-off. They either rely on computationally expensive, per-subject fine-tuning, sacrificing efficiency and zero-shot capability, or employ feed-forward architectures built on diffusio…

Cited by 0SourcecodeScholar