3 papers
cs.PL2025
Sharing State Between Prompts and Programs
Ellie Y. Cheng, Logan Weber, Tian Jin +1
The rise of large language models (LLMs) has introduced a new type of programming: natural language programming. Users write prompts, which are instructions in natural language, to…
cs.CL2025
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
Tian Jin, Ellie Y. Cheng, Zack Ankner +6
Decoding with autoregressive large language models (LLMs) traditionally occurs sequentially, generating one token after another. An emerging line of work explored parallel decoding…
cs.LG2024
Learning to Compile Programs to Neural Networks
Logan Weber, Jesse Michel, Alex Renda +1
A is a neural network that mimics the behavior of a program. Researchers have used these neural surrogates to automatically tune program in…