Author

Xingzi Xu

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Preprint Aug 2026

Trie Automata for Constrained Decoding over Large Finite Sets

The trie automaton is introduced, a specialized mechanism that exploits finite-set structure via Aho-Corasick multi-pattern matching to precompute per-node token masks, and achieves 7X faster per-step valid-token computation compared to XGrammar and 2.5X faster compilation at K>= 300.

Xingzi Xu, Karim Bouyarmane · 0 citations

#artificial intelligence Preprint Sep 2026

Extremely Sparse Supervision Incentivizes Reasoning Ability

Overall, the results challenge the assumption that effective post-training must be token-intensive and point to a new direction for understanding and designing more efficient post-training algorithms.

Zhi-Shuai Liu, Xingzi Xu, Mehmet Saygin Seyfioglu et al. · 4 citations