34 citations · 72 across the 14 of their papers we have counts for
4 papers · 1 filter
Bias Amplification in Language Model Evolution: An Iterated Learning Perspective
Yi Ren, Shangmin Guo, Linlu Qiu +2
With the widespread adoption of Large Language Models (LLMs), the prevalence of iterative interactions among these models is anticipated to increase. Notably, recent advancements i…
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
Samuel Garcin, James Doran, Shangmin Guo +2
Autonomous agents trained using deep reinforcement learning (RL) often lack the ability to successfully generalise to new environments, even when these environments share character…
Economics Arena for Large Language Models
Shangmin Guo, Haoran Bu, Haochuan Wang +4
Large language models (LLMs) have been extensively used as the backbones for general-purpose agents, and some economics literature suggest that LLMs are capable of playing various…
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning
Shangmin Guo, Yi Ren, Stefano V. Albrecht +1
Although much research has been done on proposing new models or loss functions to improve the generalisation of artificial neural networks (ANNs), less attention has been directed…