75 citations · 151 across the 18 of their papers we have counts for
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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.CL2023
The Cost of Down-Scaling Language Models: Fact Recall Deteriorates before In-Context Learning
Tian Jin, Nolan Clement, Xin Dong +4
How does scaling the number of parameters in large language models (LLMs) affect their core capabilities? We study two natural scaling techniques -- weight pruning and simply train…