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Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP

Julia Kreutzer
Stefan Riezler
Carolin Lawrence
Challenges of Real-World RL Workshop at NeurIPS 2020, Virtual

Abstract

Large volumes of interaction logs can be collected from NLP systems that are deployed in the real world. How can this wealth of information be leveraged? Using such interaction logs in an offline reinforcement learning (RL) setting is a promising approach. However, due to the nature of NLP tasks and the constraints of production systems, a series of challenges arise. We present a concise overview of these challenges and discuss possible solutions.