[Module 0] [Module 1] [Module 2] [Module 3] [Module 4] [Module 5] [Module 6]
Thursday, January 13, 2022 to Monday, January 17, 2022
Welcome to the class! In this introductory module, you will become acquainted with interactive fiction (since you’re probably too young to know what it is) and learn about the field of automated story generation (since it’s a small subfield of AI and you probably haven’t heard of it). You’ll even get a chance to make your own mini interactive fiction game the old-school way!
Academic Papers:
Peter A. Jansen, A Systematic Survey of Text Worlds as Embodied Natural Language Environments
Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew Hausknecht, Ruo Yu Tao, Layla El Asri, Mahmoud Adada, Wendy Tay, and Adam Trischler, TextWorld: A Learning Environment for Text-based Games
Matthew Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan, Interactive Fiction Games: A Colossal Adventure
Supplemental Media:
Jason Scott, GET LAMP: The Text Adventure Documentary (video, 2 hours)
Chris Ainsley/adventuron.io, Video Tutorial - Beginners Guide To Coding An Illustrated Text Adventure Game (video, 35 minutes)
Jared Sorensen, Action Castle at PAX East 2011 (video, 12 minutes)
Mark Riedl, An Introduction to AI Story Generation
H2G2.com, How to Make a Text-Based Adventure: Commands and Parser
Tuesday, January 18, 2022 to Monday, January 31, 2022
With neural language models becoming more popular within Natural Language Processing/Generation (NLP/NLG), automated story generation researchers realized how much easier it is to generate text. (And this also helped NLP researchers get interested in story generation!) Here, you’ll learn about neural language models, particularly the transformer, how to work with them, and how they are used to generate stories.
Guest Lecturer: Daphne Ippolito
Academic Papers:
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Margaret Mitchell, On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, [GPT-2 paper] Language Models are Unsupervised Multitask Learners
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, Illia Polosukhin, [Transformer paper] Attention is All You Need
Ilya Sutskever, Oriol Vinyals, Quoc V. Le, Sequence to Sequence Learning with Neural Networks
Alex Graves, Generating Sequences With Recurrent Neural Networks
Supplemental Media:
Elle Hunt (The Guardian), Tay, Microsoft’s AI chatbot, gets a crash course in racism from Twitter
Tom Simonite (Wired), The AI Text Generator That’s Too Dangerous to Make Public
Guest Lecturer: Daphne Ippolito
Academic Papers:
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, Yejin Choi, The Curious Case of Neural Text Degeneration
Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean, [word2vec paper] Efficient Estimation of Word Representations in Vector Space
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu, [T5 paper] Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Supplemental Media:
Hugh Laurie, Stephen Fry, A Bit of Fry & Laurie: Concerning Language (video, 7 minutes, 23 seconds)
Daniel Jurafsky, James H. Martin, Speech and Language Processing, Chapter 6: Vector Semantics and Embeddings
Academic Papers:
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, et al., Language Models are Few-Shot Learners (GPT-3 paper)
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, Graham Neubig, Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Attention is All You Need - presented by Marta Garcia Ferreiro & Stefan Papazov
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - presented by Salvatore Giorgi & Keith Golden
Do Massively Pretrained Language Models Make Better Storytellers? - presented by Wesley Gill, Adrian Wang, & Daniel Tao
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks - presented by Yuxuan Wang
Academic Papers:
Angela Fan, Mike Lewis, Yann Dauphin, Hierarchical Neural Story Generation
Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, Christopher D. Manning, Do Massively Pretrained Language Models Make Better Storytellers?
Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni, Green AI
Supplemental Media:
Tuesday, February 1, 2022 to Wednesday, February 10, 2021
Scripts can be considered the backbone of storytelling. They help us fill in the gaps of knowledge that we would otherwise be missing from reading a story, and they help us reason about why events happen and what order they happen in. This Module will teach you about scripts, causal chains, and events. We’ll also look at how people have been using these techniques in the age of the neural network.
Academic Papers:
Roger Schank, Robert Abelson, Scripts Plans Goals and Understanding: An Inquiry Into Human Knowledge Structures (Chapter 3: Scripts)
Karl Pichotta, Raymond Mooney, Learning Statistical Scripts with LSTM Recurrent Neural Networks
Lara J. Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison, Mark O. Riedl, Event Representations for Automated Story Generation with Deep Neural Nets
Nathanael Chambers and Dan Jurafsky, Unsupervised Learning of Narrative Schemas and their Participants
Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras, Niket Tandon, Peter Clark, Yejin Choi, proScript: Partially Ordered Scripts Generation via Pre-trained Language Models
Abhilasha Sancheti, Rachel Rudinger, What do Large Language Models Learn about Scripts?
Marie-Laure Ryan, Fiction, Non-Factuals, and the Principle of Minimal Departure
Guest Lecturer: Harry Li Zhang and Veronica Qing Lyu
Academic Papers:
Belinda Z. Li, Maxwell Nye, Jacob Andreas, Implicit Representations of Meaning in Neural Language Models
Qing Lyu, Li Zhang, Chris Callison-Burch, Goal-Oriented Script Construction
Li Zhang, Qing Lyu, Chris Callison-Burch, Reasoning about Goals, Steps, and Temporal Ordering with WikiHow
Li Zhang, Qing Lyu, Chris Callison-Burch, Intent Detection with WikiHow
Rowan Zellers, Yonatan Bisk, Roy Schwartz, Yejin Choi, SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference
Academic Papers:
Lili Yao, Nanyun Peng, Ralph Weischedel, Kevin Knight, Dongyan Zhao, Rui Yan, Plan-And-Write: Towards Better Automatic Storytelling
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, Jianfeng Gao, PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison, Mark O. Riedl, Controllable Neural Story Plot Generation via Reward Shaping
Shanshan Huang, Kenny Q. Zhu, Qianzi Liao, Libin Shen, Yinggong Zhao, Enhanced Story Representation by ConceptNet for Predicting Story Endings
Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, James Allen, A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories
Controllable Neural Story Plot Generation via Reward Shaping - presented by Ning Wan & Hongyu Zhang
Unsupervised Learning of Narrative Schemas and their Participants - presented by Ruochun Wang, Yixuan Meng, & Charles Howland
PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking - presented by Anshul Wadhawan, Karmanya Aggarwal, & Pooja Dattatri
Academic Papers:
Tuesday, February 15, 2022 to Monday, February 28, 2022
Academic Papers:
Supplemental Media:
Academic Papers:
Supplemental Media:
Peter Norvig and Stuart J. Russell, Artificial Intelligence: A Modern Approach, Chapter 11
Wikipedia, Stanford Research Institute Problem Solver
Kory Becker, Artificial Intelligence Planning with STRIPS, A Gentle Introduction
Guest Lecturer: Stephen G. Ware
Academic Papers:
Michael Lebowitz, Story-Telling as Planning and Learning
Mark O. Riedl, R. Michael Young, Open-world planning for story generation
R. Michael Young, Stephen Ware, Brad Cassell, Justus Robertson, Plans and planning in narrative generation: a review of plan-based approaches to the generation of story, discourse and interactivity in narratives
Julie Porteous, Marc Cavazza, Controlling narrative generation with planning trajectories: The role of constraints
Stephen G. Ware, Cory Siler, Sabre: A Narrative Planner Supporting Intention and Deep Theory of Mind
Stephen G. Ware, R. Michael Young, Glaive: A State-Space Narrative Planner Supporting Intentionality and Conflict
Mihai Polceanu, Julie Porteous, Alan Lindsay, Marc Cavazza, Narrative Plan Generation with Self-Supervised Learning
Michael Mateas, Andrew Stern, Integrating Plot, Character and Natural Language Processing in the Interactive Drama Façade
Manu Sharma, Santiago Ontañón, Manish Mehta, Ashwin Ram, Drama Management and Player Modeling for Interactive Fiction Games
Stephen G. Ware, Edward T. Garcia, Alireza Shirvani, Rachelyn Farrell, Multi-Agent Narrative Experience Management as Story Graph Pruning
Supplemental Media:
Story Telling as Planning and Learning - presented by Haoyu Wang
Drama Management and Player Modeling for Interactive Fiction Games - presented by Benjamin Demers & Saurabh Shah
Integrating Plot, Character and Natural Language Processing in the Interactive Drama Façade - presented by Adrian Binkley
Controlling narrative generation with planning trajectories: The role of constraints - presented by Paul Scott & Andrew Zhao
Academic Papers:
Md Sultan Al Nahian, Spencer Frazier, Mark Riedl, Brent Harrison, Learning Norms from Stories: A Prior for Value Aligned Agents
Markus Eger, Kory W. Mathewson, dAIrector: Automatic Story Beat Generation through Knowledge Synthesis
Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth, Joint Constrained Learning for Event-Event Relation Extraction
Supplemental Media:
Michael Mateas, Andrew Stern, Façade
Michael S. Gentry, Anchorhead
William Wallace Cook, PLOTTO: A New Method of Plot Suggestion for Writers of Creative Fiction
Tuesday, March 1, 2022 to Tuesday, March 22, 2022
Academic Papers:
David Gunning, Machine Common Sense Concept Paper
Kathy Panton, Cynthia Matuszek, Douglas Lenat, Dave Schneider, Michael Witbrock, Nick Siegel, and Blake Shepard, Common Sense Reasoning – From Cyc to Intelligent Assistant
Shane Storks, Qiaozi Gao, Joyce Y. Chai, Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches
Yejin Choi, Vered Shwartz, Maarten Sap, Antoine Bosselut, Dan Roth, ACL 2020 Commonsense Tutorial
Gabor Angeli and Chris Manning, NaturalLI: Natural Logic Inference for Common Sense Reasoning
Supplemental Media:
Academic Papers:
Robyn Speer, Joshua Chin, Catherine Havasi, ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
Martha Palmer, Claire Bonial, Jena Hwang, VerbNet: Capturing English verb behavior, meaning and usage
Christiane Fellbaum, WordNet
Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, David Buchanan, Lauren Berkowitz, Or Biran, Jennifer Chu-Carroll, GLUCOSE: GeneraLized and COntextualized Story Explanations
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi, ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
Zhongyang Li, Xiao Ding, Ting Liu, J. Edward Hu, Benjamin Van Durme, Guided Generation of Cause and Effect
Peter Clark, Bhavana Dalvi, Niket Tandon, What Happened? Leveraging VerbNet to Predict the Effects of Actions in Procedural Text
Lei Shi and Rada Mihalcea, Putting Pieces Together: Combining FrameNet, VerbNet and WordNet for Robust Semantic Parsing
Guest Lecturer: Susan Brown
Academic Papers:
ConceptNet 5.5: An Open Multilingual Graph of General Knowledge - presented by Weiqiu You, Yifei Li, & Yukai Yang
Machine Common Sense Concept Paper - presented by Manni Arora & Yongzhe Zhu
NaturalLI: Natural Logic Inference for Common Sense Reasoning - presented by Xuanyu Wu, Zhaoyi Hou, & Xinyue Wang
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning - presented by Xiaofeng Wang, Zhihang Yuan, & Tianyi Zhang
Academic Papers:
Supplemental Media:
Thursday, March 24, 2022 to Monday, April 4, 2022
Academic Papers:
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio, Aaron Courville, Joelle Pineau, Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, Bill Dolan, A Diversity-Promoting Objective Function for Neural Conversation Models
Oriol Vinyals, Quoc Le, A Neural Conversational Model
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan, DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
Jack Urbanek, Angela Fan, Siddharth Karamcheti, Saachi Jain, Samuel Humeau, Emily Dinan, Tim Rocktäschel, Douwe Kiela, Arthur Szlam, Jason Weston, Learning to Speak and Act in a Fantasy Text Adventure Game
Wai Man Si, Prithviraj Ammanabrolu, Mark O. Riedl, Telling Stories through Multi-User Dialogue by Modeling Character Relations
Shrimai Prabhumoye, Margaret Li, Jack Urbanek, Emily Dinan, Douwe Kiela, Jason Weston, Arthur Szlam, I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-oriented dialogue agents
Academic Papers:
Annie Louis, Charles Sutton, Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts
Maarten Sap, Marcella Cindy Prasettio, Ari Holtzman, Hannah Rashkin, Yejin Choi, Connotation Frames of Power and Agency in Modern Films
James Ryan, Curating Simulated Storyworlds
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation - presented by Zhihua Zhang, Zach (Zichen) Li, & Anish Neervannan
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models - presented by Kenneth Schumacher, Matthew Burke, & Ke Zhao
I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-oriented dialogue agents - presented by Enora Rice, Kennedy Ellison, & Anna Nixon
Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts - presented by Elizabeth Dinella & Alexander Feng
Academic Papers:
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, Jason Weston, Recipes for Building an Open-Domain Chatbot
Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, Quoc V. Le, Towards a Human-like Open-Domain Chatbot
Joao Sedoc, Daphne Ippolito, Arun Kirubarajan, Jai Thirani, Lyle Ungar, Chris Callison-Burch, ChatEval: A Tool for Chatbot Evaluation
Tuesday, April 5, 2022 to Tuesday, April 26, 2022
No homework for this module.
Guest Lecturer: Prithviraj (Raj) Ammanabrolu
Academic Papers:
Prithviraj Ammanabrolu, Mark Riedl, Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning
Prithviraj Ammanabrolu, Ethan Tien, Zhaochen Luo, Mark O. Riedl, How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds
Karthik Narasimhan, Tejas Kulkarni, Regina Barzilay, Language Understanding for Text-based Games Using Deep Reinforcement Learning
Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Deep Reinforcement Learning with a Natural Language Action Space
Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor, Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Academic Papers:
Guest Lecturer: Jonathan May
Academic Papers:
Hyundong Cho and Jonathan May, Grounding Conversations with Improvised Dialogues
Xusen Yin, Ralph Weischedel, Jonathan May, Learning to Generalize for Sequential Decision Making
Boyd Branch, Piotr Mirowski, Kory W. Mathewson, Collaborative Storytelling with Human Actors and AI Narrators
Brian Magerko, Waleed Manzoul, Mark Riedl, Allan Baumer, Daniel Fuller, Kurt Luther, Celia Pearce, An empirical study of cognition and theatrical improvisation
Lara J. Martin, Brent Harrison, and Mark O. Riedl, Improvisational Computational Storytelling in Open Worlds
Guest Lecturer: Elizabeth Clark
Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences - presented by Jong-Min Choi & Joongwon Kim
Deep Reinforcement Learning with a Natural Language Action Space - presented by Leon Zhou
Academic Papers:
Asli Celikyilmaz, Elizabeth Clark, Jianfeng Gao, Evaluation of Text Generation: A Survey
Elizabeth Clark, Tal August, Sofia Serrano, Nikita Haduong, Suchin Gururangan, Noah A. Smith, All That’s ‘Human’ Is Not Gold: Evaluating Human Evaluation of Generated Text
Sebastian Gehrmann, Elizabeth Clark, Thibault Sellam, Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text
Christopher Purdy, Xinyu Wang, Larry He, Mark Riedl, Predicting Generated Story Quality with Quantitative Measures
Morteza Behrooz, Justus Robertson, Arnav Jhala, Story Quality as a Matter of Perception: Using Word Embeddings to Estimate Cognitive Interest
Elizabeth Clark, Noah A. Smith, Choose Your Own Adventure: Paired Suggestions in Collaborative Writing for Evaluating Story Generation Models
Chin-Yew Lin, ROUGE: A Package for Automatic Evaluation of Summaries
Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger, From Word Embeddings To Document Distances
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi, BERTScore: Evaluating Text Generation with BERT
Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang, Unifying Human and Statistical Evaluation for Natural Language Generation
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, Yong Yu, Texygen: A Benchmarking Platform for Text Generation Models
Thibault Sellam, Dipanjan Das, Ankur Parikh, BLEURT: Learning Robust Metrics for Text Generation
Jian Guan, Minlie Huang, UNION: An Unreferenced Metric for Evaluating Open-ended Story Generation
David M. Howcroft, et al., Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, Jianfeng Gao, PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
Elizabeth Clark, Anne Spencer Ross, Chenhao Tan, Yangfeng Ji, Noah A. Smith, Creative Writing with a Machine in the Loop: Case Studies on Slogans and Stories
Reid Swanson, Andrew S. Gordon, Say Anything: Using Textual Case-Based Reasoning to Enable Open-Domain Interactive Storytelling
Nader Akoury, Shufan Wang, Josh Whiting, Stephen Hood, Nanyun Peng, Mohit Iyyer, STORIUM: A Dataset and Evaluation Platform for Machine-in-the-Loop Story Generation
Mina Lee, Percy Liang, Qian Yang, CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities
Guest Lecturer: Ting-Hao Kenneth Huang
Academic Papers:
Chi-Yang Hsu, Yun-Wei Chu, Tsai-Lun Yang, Ting-Hao Huang, Lun-Wei Ku, Stretch-VST: Getting Flexible With Visual Stories
Chi-Yang Hsu, Yun-Wei Chu, Ting-Hao ‘Kenneth’ Huang, Lun-Wei Ku, Plot and Rework: Modeling Storylines for Visual Storytelling
Mohit Iyyer, Varun Manjunatha, Anupam Guha, Yogarshi Vyas, Jordan Boyd-Graber, Hal Daume III, Larry S. Davis, The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives
Ting-Hao Kenneth Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, and Margaret Mitchell, Visual Storytelling
Yukun Zhu, Ryan Kiros, Richard Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler, Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books