3 papers
cs.LG2026
Intent-aligned Formal Specification Synthesis via Traceable Refinement
Zhe Ye, Aidan Z. H. Yang, Huangyuan Su +6
Large language models are increasingly used to generate code from natural language, but ensuring correctness remains challenging. Formal verification offers a principled way to obt…
cs.LG2026
Learning Adaptive LLM Decoding
Chloe H. Su, Zhe Ye, Samuel Tenka +3
Decoding from large language models (LLMs) typically relies on fixed sampling hyperparameters (e.g., temperature, top-p), despite substantial variation in task difficulty and uncer…
cs.PL2024
VERT: Verified Equivalent Rust Transpilation with Large Language Models as Few-Shot Learners
Aidan Z. H. Yang, Yoshiki Takashima, Brandon Paulsen +2
Rust is a programming language that combines memory safety and low-level control, providing C-like performance while guaranteeing the absence of undefined behaviors by default. Rus…