Papers with reinforcement learning problems
Deep Reinforcement Learning for NLP (P18-5)
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| Challenge: | Many natural language processing tasks can be formulated as deep reinforcement learning (DRL) problems. |
| Approach: | This tutorial provides an introduction to the foundations of deep reinforcement learning . it describes recent advances in designing deep reinforcement for NLP . |
| Outcome: | This tutorial provides an introduction to the foundations of deep reinforcement learning and some practical solutions for NLP tasks. |
Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning (2025.findings-emnlp)
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| Challenge: | Instruction-fine-tuned large language models (LLMs) under 14B parameters underperform on NLU tasks . we explore a framework to improve the NLU capabilities of LLMs . |
| Approach: | They propose to use Proximal Policy Optimization to improve NLU capabilities . they frame NLU as a reinforcement learning environment and optimize for reward signals . |
| Outcome: | The proposed framework outperforms supervised fine-tuning on GLUE and superGLUE tasks. |