Papers with Hybrid systems
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 . |
Neural Grammatical Error Correction with Finite State Transducers (N19-1)
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| Challenge: | Language model based GEC (LM-GEC) is a promising alternative to SMT and neural sequence-to-sequence models. |
| Approach: | They propose to use finite state transducers to improve LM-GEC by rescoring with neural language models. |
| Outcome: | The proposed model outperforms the best published results on the CoNLL-2014 test set and achieves far better relative improvements over the baselines. |