drl4nlp.scratchpad

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Policy Gradients

• buck_arxiv17: Ask the Right Questions: Active Question Reformulation with Reinforcement Learning [arXiv]
• dhingra_acl17: Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access [arXiv] [code]
• paulus_arxiv17: A Deep Reinforced Model for Abstractive Summarization [arXiv]
• nogueira_arxiv17: Task-Oriented Query Reformulation with Reinforcement Learning [arXiv] [code]
• li_iclr17: Dialog Learning with Human-in-the-loop [arXiv] [code]
• li_iclr17_2: Learning through dialogue interactions by asking questions [arXiv] [code]
• yogatama_iclr17: Learning to Compose Words into Sentences with Reinforcement Learning [arXiv]
• dinu_nips16w: Reinforcement Learning for Transition-Based Mention Detection [arXiv]
• clark_emnlp16: Deep Reinforcement Learning for Mention-Ranking Coreference models [arXiv] [code]

Value Function

• narasimhan_emnlp16: Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning [arXiv] [code]

Misc

• bordes_iclr17: Learning End-to-End Goal-Oriented Dialog [arXiv]
• weston_nips16: Dialog-based Language Learning [arXiv] [code]
• nogueira_nips16: End-to-End Goal-Driven Web Navigation [arXiv] [code]