80 citations · 195 across the 20 of their papers we have counts for
7 papers · 1 filter
Making Large Language Models into World Models with Precondition and Effect Knowledge
Kaige Xie, Ian Yang, John Gunerli +1
World models, which encapsulate the dynamics of how actions affect environments, are foundational to the functioning of intelligent agents. In this work, we explore the potential o…
Ambient Adventures: Teaching ChatGPT on Developing Complex Stories
Zexin Chen, Eric Zhou, Kenneth Eaton +2
Imaginative play is an area of creativity that could allow robots to engage with the world around them in a much more personified way. Imaginary play can be seen as taking real obj…
Dialogue Shaping: Empowering Agents through NPC Interaction
Wei Zhou, Xiangyu Peng, Mark Riedl
One major challenge in reinforcement learning (RL) is the large amount of steps for the RL agent needs to converge in the training process and learn the optimal policy, especially…
Goal-Directed Story Generation: Augmenting Generative Language Models with Reinforcement Learning
Amal Alabdulkarim, Winston Li, Lara J. Martin +1
The advent of large pre-trained generative language models has provided a common framework for AI story generation via sampling the model to create sequences that continue the stor…
Automated Story Generation as Question-Answering
Louis Castricato, Spencer Frazier, Jonathan Balloch +2
Neural language model-based approaches to automated story generation suffer from two important limitations. First, language model-based story generators generally do not work towar…
Reframing Human-AI Collaboration for Generating Free-Text Explanations
Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta +2
Large language models are increasingly capable of generating fluent-appearing text with relatively little task-specific supervision. But can these models accurately explain classif…