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cs.AI2026
Constrained Adaptive Rejection Sampling
PaweÅ Parys, Sairam Vaidya, Taylor Berg-Kirkpatrick +1
Language Models (LMs) are increasingly used in applications where generated outputs must satisfy strict semantic or syntactic constraints. Existing approaches to constrained genera…
cs.AI2025
Grammar-Aligned Decoding
Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick +2
Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code, mathematical formulas, or well-formed markup. Constrained decoding a…
cs.AI2025
Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
Emmanuel Anaya Gonzalez, Sairam Vaidya, Kanghee Park +3
Constrained decoding enables Language Models (LMs) to produce samples that provably satisfy hard constraints. However, existing constrained-decoding approaches often distort the un…