19 citations · 19 across the 1 of their papers we have counts for
2 papers
cs.AI2022★ 19 cited
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
Chan Hee Song, Jiaman Wu, Clayton Washington +3
This study focuses on using large language models (LLMs) as a planner for embodied agents that can follow natural language instructions to complete complex tasks in a visually-perc…
cs.CL2022
Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again
Bernal Jiménez Gutiérrez, Nikolas McNeal, Clay Washington +4
The strong few-shot in-context learning capability of large pre-trained language models (PLMs) such as GPT-3 is highly appealing for application domains such as biomedicine, which…