Event Representations for Automated Story Generation with Deep Neural Nets. - Lara J. Martin; Prithviraj Ammanabrolu; William Hancock; Shruti Singh; Brent Harrison; Mark O. Riedl (CoRR, 2017)

Event Representations for Automated Story Generation with Deep Neural Nets. - Lara J. Martin; Prithviraj Ammanabrolu; Xinyu Wang; William Hancock; Shruti Singh; Brent Harrison; Mark O. Riedl (AAAI, 2018)

Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning. - Prithviraj Ammanabrolu; Mark O. Riedl (NAACL-HLT (1), 2019)

Transfer in Deep Reinforcement Learning Using Knowledge Graphs. - Prithviraj Ammanabrolu; Mark O. Riedl (TextGraphs@EMNLP, 2019)

Story Realization: Expanding Plot Events into Sentences. - Prithviraj Ammanabrolu; Ethan Tien; Wesley Cheung; Zhaochen Luo; William Ma; Lara J. Martin; Mark O. Riedl (AAAI, 2020)

Interactive Fiction Games: A Colossal Adventure. - Matthew J. Hausknecht; Prithviraj Ammanabrolu; Marc-Alexandre Côté; Xingdi Yuan (AAAI, 2020)

Bringing Stories Alive: Generating Interactive Fiction Worlds. - Prithviraj Ammanabrolu; Wesley Cheung; Dan Tu; William Broniec; Mark O. Riedl (AIIDE, 2020)

Toward Automated Quest Generation in Text-Adventure Games. - Prithviraj Ammanabrolu; William Broniec; Alex Mueller; Jeremy Paul; Mark O. Riedl (ICCC, 2020)

Graph Constrained Reinforcement Learning for Natural Language Action Spaces. - Prithviraj Ammanabrolu; Matthew J. Hausknecht (ICLR, 2020)

How To Avoid Being Eaten By a Grue: Exploration Strategies for Text-Adventure Agents. - Prithviraj Ammanabrolu; Ethan Tien; Zhaochen Luo; Mark O. Riedl (CoRR, 2020)

How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds. - Prithviraj Ammanabrolu; Ethan Tien; Matthew J. Hausknecht; Mark O. Riedl (CoRR, 2020)

Playing Text-Based Games with Common Sense. - Sahith N. Dambekodi; Spencer Frazier; Prithviraj Ammanabrolu; Mark O. Riedl (CoRR, 2020)

Automated Storytelling via Causal, Commonsense Plot Ordering. - Prithviraj Ammanabrolu; Wesley Cheung; William Broniec; Mark O. Riedl (AAAI, 2021)

How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds. - Prithviraj Ammanabrolu; Jack Urbanek; Margaret Li; Arthur Szlam; Tim Rocktäschel; Jason Weston (NAACL-HLT, 2021)

Learning Knowledge Graph-based World Models of Textual Environments. - Prithviraj Ammanabrolu; Mark O. Riedl (NeurIPS, 2021)

Modeling Worlds in Text. - Prithviraj Ammanabrolu; Mark O. Riedl (NeurIPS Datasets and Benchmarks, 2021)

Telling Stories through Multi-User Dialogue by Modeling Character Relations. - Wai Man Si; Prithviraj Ammanabrolu; Mark O. Riedl (SIGDIAL, 2021)

Situated language learning via interactive narratives. - Prithviraj Ammanabrolu; Mark O. Riedl (Patterns, 2021)

Language Learning in Interactive Environments. - Prithviraj Ammanabrolu (2021)

Situated Dialogue Learning through Procedural Environment Generation. - Prithviraj Ammanabrolu; Renee Jia; Mark O. Riedl (ACL (1), 2022)

ScienceWorld: Is your Agent Smarter than a 5th Grader? - Ruoyao Wang; Peter A. Jansen; Marc-Alexandre Côté; Prithviraj Ammanabrolu (EMNLP, 2022)

Aligning to Social Norms and Values in Interactive Narratives. - Prithviraj Ammanabrolu; Liwei Jiang; Maarten Sap; Hannaneh Hajishirzi; Yejin Choi 001 (NAACL-HLT, 2022)

QUARK: Controllable Text Generation with Reinforced Unlearning. - Ximing Lu; Sean Welleck; Jack Hessel; Liwei Jiang; Lianhui Qin; Peter West; Prithviraj Ammanabrolu; Yejin Choi 001 (NeurIPS, 2022)

Inherently Explainable Reinforcement Learning in Natural Language. - Xiangyu Peng; Mark O. Riedl; Prithviraj Ammanabrolu (NeurIPS, 2022)

Multimodal Knowledge Alignment with Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Prithviraj Ammanabrolu; Rowan Zellers; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CoRR, 2022)

An AI Dungeon Master's Guide: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons. - Pei Zhou; Andrew Zhu; Jennifer Hu 001; Jay Pujara; Xiang Ren 001; Chris Callison-Burch; Yejin Choi 001; Prithviraj Ammanabrolu (CoRR, 2022)

I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons. - Pei Zhou; Andrew Zhu; Jennifer Hu 001; Jay Pujara; Xiang Ren 001; Chris Callison-Burch; Yejin Choi 001; Prithviraj Ammanabrolu (ACL (1), 2023)

Fusing Pre-Trained Language Models with Multimodal Prompts through Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Rowan Zellers; Prithviraj Ammanabrolu; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CVPR, 2023)

Behavior Cloned Transformers are Neurosymbolic Reasoners. - Ruoyao Wang; Peter Jansen 001; Marc-Alexandre Côté; Prithviraj Ammanabrolu (EACL, 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - Ximing Lu; Faeze Brahman; Peter West; Jaehun Jung; Khyathi Raghavi Chandu; Abhilasha Ravichander; Prithviraj Ammanabrolu; Liwei Jiang; Sahana Ramnath; Nouha Dziri; Jillian Fisher; Bill Y. Lin; et al. (EMNLP, 2023)

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization. - Rajkumar Ramamurthy; Prithviraj Ammanabrolu; Kianté Brantley; Jack Hessel; Rafet Sifa; Christian Bauckhage; Hannaneh Hajishirzi; Yejin Choi 001 (ICLR, 2023)

Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling. - Kolby Nottingham; Prithviraj Ammanabrolu; Alane Suhr; Yejin Choi 001; Hannaneh Hajishirzi; Sameer Singh 001; Roy Fox (ICML, 2023)

SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks. - Bill Yuchen Lin; Yicheng Fu; Karina Yang; Faeze Brahman; Shiyu Huang 001; Chandra Bhagavatula; Prithviraj Ammanabrolu; Yejin Choi 001; Xiang Ren 001 (NeurIPS, 2023)

Fine-Grained Human Feedback Gives Better Rewards for Language Model Training. - Zeqiu Wu; Yushi Hu; Weijia Shi; Nouha Dziri; Alane Suhr; Prithviraj Ammanabrolu; Noah A. Smith; Mari Ostendorf; Hannaneh Hajishirzi (NeurIPS, 2023)

Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging. - Joel Jang; Seungone Kim; Bill Yuchen Lin; Yizhong Wang; Jack Hessel; Luke Zettlemoyer; Hannaneh Hajishirzi; Yejin Choi 001; Prithviraj Ammanabrolu (CoRR, 2023)

InSCIt: Information-Seeking Conversations with Mixed-Initiative Interactions. - Zeqiu Wu; Ryu Parish; Hao Cheng 002; Sewon Min; Prithviraj Ammanabrolu; Mari Ostendorf; Hannaneh Hajishirzi (Trans. Assoc. Comput. Linguistics, 2023)

CPS-TaskForge: Generating Collaborative Problem Solving Environments for Diverse Communication Tasks. - Nikita Haduong; Irene Wang; Bo-Ru Lu; Prithviraj Ammanabrolu; Noah A. Smith (CoRR, 2024)

Critique-out-Loud Reward Models. - Zachary Ankner; Mansheej Paul; Brandon Cui; Jonathan D. Chang; Prithviraj Ammanabrolu (CoRR, 2024)

A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models. - Zhouhang Xie; Junda Wu; Yiran Shen 004; Yu Xia 007; Xintong Li 001; Aaron Chang; Ryan A. Rossi; Sachin Kumar; Bodhisattwa Prasad Majumder; Jingbo Shang; Prithviraj Ammanabrolu; Julian J. McAuley (CoRR, 2025)

TALES: Text Adventure Learning Environment Suite. - Christopher Zhang Cui; Xingdi Yuan; Ziang Xiao; Prithviraj Ammanabrolu; Marc-Alexandre Côté (CoRR, 2025)

In-context Ranking Preference Optimization. - Junda Wu; Rohan Surana; Zhouhang Xie; Yiran Shen 004; Yu Xia 007; Tong Yu 001; Ryan A. Rossi; Prithviraj Ammanabrolu; Julian J. McAuley (CoRR, 2025)

Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning. - Isadora White; Kolby Nottingham; Ayush Maniar; Max Robinson; Hansen Lillemark; Mehul Maheshwari; Lianhui Qin; Prithviraj Ammanabrolu (CoRR, 2025)

Beyond Needle(s) in the Embodied Haystack: Environment, Architecture, and Training Considerations for Long Context Reasoning. - Bosung Kim; Prithviraj Ammanabrolu (CoRR, 2025)