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Found 5 papers, 2 papers with code
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
We investigate the setup of "Parameter Efficient Reinforcement Learning" (PERL), in which we perform reward model training and reinforcement learning using LoRA.
Faithful Persona-based Conversational Dataset Generation with Large Language Models
Training Natural Language Processing (NLP) models on a diverse and comprehensive persona-based dataset can lead to conversational models that create a deeper connection with the user, and maintain their engagement.
Leveraging Large Language Models in Conversational Recommender Systems
A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue.
Efficient and Private Federated Learning with Partially Trainable Networks
Through extensive experiments, we empirically show that Federated learning of Partially Trainable neural networks (FedPT) can result in superior communication-accuracy trade-offs, with up to $46\times$ reduction in communication cost, at a small accuracy cost.
Federated Reconstruction: Partially Local Federated Learning
We also describe the successful deployment of this approach at scale for federated collaborative filtering in a mobile keyboard application.
