constrained-generation

LatticeBridge proposes a twisted sequential Monte Carlo decoder for structured sequence generation that improves constraint satisfaction by treating the problem as rare-event inference, outperforming greedy and beam baselines on CommonGen, E2E NLG, and WikiBio.

This paper presents a system for constrained humor generation that uses a generate-many select-best strategy with a preference model learned from human comparisons. It achieved top ranks in English and Chinese subtasks and second in Spanish at SemEval-2026 Task 1.