17 citations · 43 across the 11 of their papers we have counts for
6 papers · 1 filter
Machine Learning Approaches for Principle Prediction in Naturally Occurring Stories
Md Sultan Al Nahian, Spencer Frazier, Brent Harrison +1
Value alignment is the task of creating autonomous systems whose values align with those of humans. Past work has shown that stories are a potentially rich source of information on…
Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning
Louis Castricato, Alexander Havrilla, Shahbuland Matiana +5
Controlled automated story generation seeks to generate natural language stories satisfying constraints from natural language critiques or preferences. Existing methods to control…
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…
Cut the CARP: Fishing for zero-shot story evaluation
Shahbuland Matiana, JR Smith, Ryan Teehan +4
Recent advances in large-scale language models (Raffel et al., 2019; Brown et al., 2020) have brought significant qualitative and quantitative improvements in machine-driven text g…
Fabula Entropy Indexing: Objective Measures of Story Coherence
Louis Castricato, Spencer Frazier, Jonathan Balloch +1
Automated story generation remains a difficult area of research because it lacks strong objective measures. Generated stories may be linguistically sound, but in many cases suffer…
Reducing Non-Normative Text Generation from Language Models
Xiangyu Peng, Siyan Li, Spencer Frazier +1
Large-scale, transformer-based language models such as GPT-2 are pretrained on diverse corpora scraped from the internet. Consequently, they are prone to generating non-normative t…