30 citations · 69 across the 17 of their papers we have counts for
11 papers · 1 filter
Self-Directed Synthetic Dialogues and Revisions Technical Report
Nathan Lambert, Hailey Schoelkopf, Aaron Gokaslan +3
Synthetic data has become an important tool in the fine-tuning of language models to follow instructions and solve complex problems. Nevertheless, the majority of open data to date…
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
Suppressing Pink Elephants with Direct Principle Feedback
Louis Castricato, Nathan Lile, Suraj Anand +3
Existing methods for controlling language models, such as RLHF and Constitutional AI, involve determining which LLM behaviors are desirable and training them into a language model.…
EleutherAI: Going Beyond "Open Science" to "Science in the Open"
Jason Phang, Herbie Bradley, Leo Gao +2
Over the past two years, EleutherAI has established itself as a radically novel initiative aimed at both promoting open-source research and conducting research in a transparent, op…
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…
Linearly Mapping from Image to Text Space
Jack Merullo, Louis Castricato, Carsten Eickhoff +1
The extent to which text-only language models (LMs) learn to represent features of the non-linguistic world is an open question. Prior work has shown that pretrained LMs can be tau…
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…
Parameter-Efficient Neural Question Answering Models via Graph-Enriched Document Representations
Louis Castricato, Stephen Fitz, Won Young Shin
As the computational footprint of modern NLP systems grows, it becomes increasingly important to arrive at more efficient models. We show that by employing graph convolutional docu…
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…
Towards a Formal Model of Narratives
Louis Castricato, Stella Biderman, Rogelio E. Cardona-Rivera +1
In this paper, we propose the beginnings of a formal framework for modeling narrative \textit{qua} narrative. Our framework affords the ability to discuss key qualities of stories…