26 citations · 30 across the 6 of their papers we have counts for
7 papers
Fabula: Building a Narrative Storytelling Sidekick with the Writers' Community
Piotr Mirowski, Ben Wedin, Reinald Kim Amplayo +14
We design and evaluate Fabula, an interactive app for fiction writers. Fabula uses detailed narrative plans informed by general narratological theory. Stories are structured hierar…
ConstitutionalExperts: Training a Mixture of Principle-based Prompts
Savvas Petridis, Ben Wedin, Ann Yuan +2
Large language models (LLMs) are highly capable at a variety of tasks given the right prompt, but writing one is still a difficult and tedious process. In this work, we introduce C…
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles
Savvas Petridis, Ben Wedin, James Wexler +5
Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot's outputs, su…
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
Scott Sanner, Krisztian Balog, Filip Radlinski +2
Traditional recommender systems leverage users' item preference history to recommend novel content that users may like. However, modern dialog interfaces that allow users to expres…
On Natural Language User Profiles for Transparent and Scrutable Recommendation
Filip Radlinski, Krisztian Balog, Fernando Diaz +2
Natural interaction with recommendation and personalized search systems has received tremendous attention in recent years. We focus on the challenge of supporting people's understa…
IMACS: Image Model Attribution Comparison Summaries
Eldon Schoop, Ben Wedin, Andrei Kapishnikov +2
Developing a suitable Deep Neural Network (DNN) often requires significant iteration, where different model versions are evaluated and compared. While metrics such as accuracy are…
Guided Integrated Gradients: An Adaptive Path Method for Removing Noise
Andrei Kapishnikov, Subhashini Venugopalan, Besim Avci +3
Integrated Gradients (IG) is a commonly used feature attribution method for deep neural networks. While IG has many desirable properties, the method often produces spurious/noisy p…