184 citations · 393 across the 5 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2024
In-Context Learning with Long-Context Models: An In-Depth Exploration
Amanda Bertsch, Maor Ivgi, Emily Xiao +4
As model context lengths continue to increase, the number of demonstrations that can be provided in-context approaches the size of entire training datasets. We study the behavior o…
cs.CL2024★ 3 cited
In-Context Principle Learning from Mistakes
Tianjun Zhang, Aman Madaan, Luyu Gao +5
In-context learning (ICL, also known as few-shot prompting) has been the standard method of adapting LLMs to downstream tasks, by learning from a few input-output examples. Nonethe…
cs.CL2022★ 5 cited
Language Models of Code are Few-Shot Commonsense Learners
Aman Madaan, Shuyan Zhou, Uri Alon +2
We address the general task of structured commonsense reasoning: given a natural language input, the goal is to generate a graph such as an event -- or a reasoning-graph. To employ…