2026
Logit‑KL Flow Matching: Non‑Autoregressive Text Generation via Sampling‑Hybrid Inference
ICLR 2026poster
Non-autoregressive (NAR) language models offer notable efficiency in text generation by circumventing the sequential bottleneck of autoregressive decoding. However, accurately modeling dependencies in discrete sequences remains challenging in this paradigm. In this work, we advance the field of NAR…