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Self-Rewarding Sequential Monte Carlo for Masked Diffusion Language Models
Self-rewarding sequential Monte Carlo improves masked diffusion language model sampling via trajectory-level confidence weights across parallel particles, boosting quality without training.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 5 on Hugging Face · Code ★ 16
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strict 0/5