We introduce a novel prompting framework called Directional Stimulus Prompting for guiding black-box large language models (LLMs) toward desired outputs. The framework introduces a new component called directional stimulus into the prompt, providing more fine-grained guidance and control over LLMs....
论文分享:Guiding Pretraining in Reinforcement Learning with Large Language Models 这篇文章主要研究的问题领域是无监督强化学习(URL),即如何在缺乏奖励函数的情况下,通过intrinsic reward对环境进行探索。本文提出的方法ELLM(Exploring with LLMs),利用LLM给出建议目标,引导策略预训练,让agent做出更多看起来对人类有意...
Guiding Pretraining in Reinforcement Learning with Large Language Models 2023.02 Berkeley, MIT, UW的研究 by tanh 简略版 现有强化学习方法会随机扰动动作或策略参数,来做无方向的探索,这很难成功 intrinsically motivated RL:探索outcomes,而不是action。因为很多差动作,对应到同一个结果:比如摔跤 人类不会均匀地...
代码仓库 Guiding Pretraining in Reinforcement Learning with Large Language Models
CoG-DQA: Chain-of-Guiding Learning with Large Language Models for Diagram Question Answering Supplementary Material 1. Design of the Guiding Head As mentioned in the main part, in order to ensure the diver- sity of prompts, we manually define five different guiding heads for ea...
Moreover, to enhance the interpretability of prediction results in bispecific target combination, we combined machine learning models with Large Language Models (LLMs). Through a Retrieval-Augmented Generation (RAG) approach, we supplement each pair of bispecific targets' machine learning prediction with...
"In a world where 80% of information is unstructured, traditional methods of analysis only scratch the surface," saidEric Sydell, PhD, CEO and co-founder of Vero AI. "Using large language models (LLMs) and other statistical techniques, Ver...
values will be incorporated into any amended rules on judicial interpretation work. The Supreme People’s Procuratorate (SPP) revised itsruleson judicial interpretation work earlier this year, and it is possible that the SPC will harmonize some of the language in its rules with those of the SPP...
Chain-of-Thought (CoT) prompting along with sub-question generation and answering has enhanced multi-step reasoning capabilities of Large Language Models (LLMs). However, prompting the LLMs to directly generate sub-questions is suboptimal since they sometimes generate redundant or irrelevant questions....
Crafting effective prompts for code generation or editing with Large Language Models (LLMs) is not an easy task. Particularly, the absence of immediate, stable feedback during prompt crafting hinders effective interaction, as users are left to mentally imagine possible outcomes until the code is ge...