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I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons.

P. Zhou, A. Zhu, J. Hu, J. Pujara, X. Ren, C. Callison-Burch, Y. Choi, и P. Ammanabrolu. ACL (1), стр. 11136-11155. Association for Computational Linguistics, (2023)

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Prithviraj Sen

Другие публикации лиц с тем же именем

Interactive Fiction Games: A Colossal Adventure.M. Hausknecht, P. Ammanabrolu, M. Côté, и X. Yuan. AAAI, стр. 7903-7910. AAAI Press, (2020)Modeling Worlds in Text.P. Ammanabrolu, и M. Riedl. NeurIPS Datasets and Benchmarks, (2021)Bringing Stories Alive: Generating Interactive Fiction Worlds.P. Ammanabrolu, W. Cheung, D. Tu, W. Broniec, и M. Riedl. AIIDE, стр. 3-9. AAAI Press, (2020)Event Representations for Automated Story Generation with Deep Neural Nets.L. Martin, P. Ammanabrolu, X. Wang, W. Hancock, S. Singh, B. Harrison, и M. Riedl. AAAI, стр. 868-875. AAAI Press, (2018)Situated language learning via interactive narratives.P. Ammanabrolu, и M. Riedl. Patterns, 2 (9): 100316 (2021)Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization.R. Ramamurthy, P. Ammanabrolu, K. Brantley, J. Hessel, R. Sifa, C. Bauckhage, H. Hajishirzi, и Y. Choi. ICLR, OpenReview.net, (2023)Critique-out-Loud Reward Models.Z. Ankner, M. Paul, B. Cui, J. Chang, и P. Ammanabrolu. CoRR, (2024)How To Avoid Being Eaten By a Grue: Exploration Strategies for Text-Adventure Agents.P. Ammanabrolu, E. Tien, Z. Luo, и M. Riedl. CoRR, (2020)Learning Knowledge Graph-based World Models of Textual Environments.P. Ammanabrolu, и M. Riedl. NeurIPS, стр. 3720-3731. (2021)Inherently Explainable Reinforcement Learning in Natural Language.X. Peng, M. Riedl, и P. Ammanabrolu. NeurIPS, (2022)

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Prithviraj Sen

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