GoKawiilContinuous diffusion language models see renewed research momentum
A wave of new research papers is reviving interest in continuous diffusion techniques for language generation, an approach that had largely been overtaken by discrete diffusion and autoregressive methods in recent years. The author reviews this resurgence, tracing why continuous diffusion for text fell out of favor and why several research groups are now revisiting it as an alternative to token-by-token autoregressive generation.