4 papers
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…
Flexible and Efficient Grammar-Constrained Decoding
Kanghee Park, Timothy Zhou, Loris D'Antoni
Large Language Models (LLMs) are often asked to generate structured outputs that obey precise syntactic rules, such as code snippets or formatted data. Grammar-constrained decoding…
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…
LOUD: Synthesizing Strongest and Weakest Specifications
Kanghee Park, Xuanyu Peng, Loris D'Antoni
This paper tackles the problem of synthesizing specifications for nondeterministic programs. For such programs, useful specifications can capture demonic properties, which hold for…