4 citations · 12 across the 14 of their papers we have counts for
3 papers · 1 filter
Orchestrating LLMs with Different Personalizations
Jin Peng Zhou, Katie Z Luo, Jingwen Gu +3
This paper presents a novel approach to aligning large language models (LLMs) with individual human preferences, sometimes referred to as Reinforcement Learning from \textit{Person…
On Speeding Up Language Model Evaluation
Jin Peng Zhou, Christian K. Belardi, Ruihan Wu +4
Developing prompt-based methods with Large Language Models (LLMs) requires making numerous decisions, which give rise to a combinatorial search problem over hyper-parameters. This…
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
Jin Peng Zhou, Charles Staats, Wenda Li +3
Large language models (LLM), such as Google's Minerva and OpenAI's GPT families, are becoming increasingly capable of solving mathematical quantitative reasoning problems. However,…