Dystruct formulates flexible-length generation in diffusion language models as a dynamic structural inference problem solved via Bayesian integration of local uncertainty and structural signals.
Dream 7b: Diffusion large language models
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Dystruct: Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference
Dystruct formulates flexible-length generation in diffusion language models as a dynamic structural inference problem solved via Bayesian integration of local uncertainty and structural signals.