Papers by Huixin Zhan
Inference-Time Feedback for Reasoning Controllability in Diffusion Language Models (2026.acl-srw)
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| Challenge: | In scientific NLP systems, model outputs often serve as interfaces to downstream systems that assume strict structural requirements. |
| Approach: | They evaluate machine-checkable controllability along three axes: structural control, iterative correction, and decoding dynamics. |
| Outcome: | The proposed model can be usefully decomposed into global structure versus local control . the proposed model improves global structure while improving iterative correction . |