ELF: Embedded Language Flows
Diffusion and flow-based models have become the de facto approaches for generating continuous data, e.g., in domains such as images and videos. Their success has attracted growing interest in applying them to language modeling. Unlike their image-domain counterparts, today's leading diffusion language models (DLMs) primarily operate over discrete tokens. In this paper, we show that continuous DLMs can be made effective with minimal adaptation to the discrete domain. We propose Embedded Language Flows (ELF), a class of diffusion models in continuous embedding space based on continuous-time Flow Matching. Unlike existing DLMs, ELF predominantly stays within the continuous embedding space un...
| Authors | Keya Hu, Linlu Qiu, Yiyang Lu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 11 May 2026 |
| Last updated at source | 26 June 2026 |
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