Tag
Flux-OPD proposes an on-policy distillation paradigm that uses evolving contexts as in-training supervision to capture task preferences in open-ended domains, outperforming existing OPD paradigms.
This paper proposes Detect–Remask–Repair, a diffusion-based framework for localized faithfulness repair in summarization when contexts evolve, and introduces the StreamSum benchmark for evaluating such settings. Experiments show it offers controllable trade-offs between faithfulness, speed, and content preservation.