6 citations · 13 across the 5 of their papers we have counts for
5 papers
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn +3
Distributed Deep Reinforcement Learning (DRL) aims to leverage more computational resources to train autonomous agents with less training time. Despite recent progress in the field…
MEMORY-VQ: Compression for Tractable Internet-Scale Memory
Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis +4
Retrieval augmentation is a powerful but expensive method to make language models more knowledgeable about the world. Memory-based methods like LUMEN pre-compute token representati…
Multi-Task End-to-End Training Improves Conversational Recommendation
Naveen Ram, Dima Kuzmin, Ellie Ka In Chio +4
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a…
Improving Fairness in Adaptive Social Exergames via Shapley Bandits
Robert C. Gray, Jennifer Villareale, Thomas B. Fox +5
Algorithmic fairness is an essential requirement as AI becomes integrated in society. In the case of social applications where AI distributes resources, algorithms often must make…
LongT5: Efficient Text-To-Text Transformer for Long Sequences
Mandy Guo, Joshua Ainslie, David Uthus +4
Recent work has shown that either (1) increasing the input length or (2) increasing model size can improve the performance of Transformer-based neural models. In this paper, we pre…