4 papers
Self-conditioned Flow Map Language Models via Fixed-point Flows
Jaehoon Yoo, Wonjung Kim, Floor Eijkelboom +4
Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditioning on its own denoising est…
Posterior Refinement: Fast Language Generation via Any-Order Flow Maps
Manan Agarwal, Sheel Shah, Chanhyuk Lee +6
Non-autoregressive generation offers a powerful paradigm for iterative refinement, allowing models to recursively critique, erase and regenerate arbitrary subsets of tokens. Howeve…
Variable-Length Tokenization via Learnable Global Merging for Diffusion Transformers
Dong Hoon Lee, Seunghoon Hong
Latent Diffusion Models (LDMs) have become dominant in visual synthesis, but their quality-compute trade-off is largely constrained by the tokenizer's fixed compression ratio. Vari…
Root-Selecting Fixed-Point Inversion for Rectified Flows via Trajectory Straightness
Semin Kim, Jihwan Yoon, Seunghoon Hong
Finding the initial noise that generates a given data sample, known as inversion, is a key component for downstream applications such as training-free image editing. Existing fixed…