4 papers
Between Predictability and Randomness: Seeking Artistic Inspiration from AI Generative Models
Olga Vechtomova
Artistic inspiration often emerges from language that is open to interpretation. This paper explores the use of AI-generated poetic lines as stimuli for creativity. Through analysi…
Extracting Information About Publication Venues Using Citation-Informed Transformers
Brian D. Zimmerman, Joshua Folkins, Olga Vechtomova
Scientific document embeddings contain a variety of rich features which can be harnessed for downstream tasks such as recommendation, ranking, and clustering. We explore which tang…
No Stupid Questions: An Analysis of Question Query Generation for Citation Recommendation
Brian D. Zimmerman, Julien Aubert-Béduchaud, Florian Boudin +2
Existing techniques for citation recommendation are constrained by their adherence to article contents and metadata. We leverage GPT-4o-mini's latent expertise as an inquisitive as…
A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches
Gaurav Sahu, Olga Vechtomova, Issam H. Laradji
Existing approaches for low-resource text summarization primarily employ large language models (LLMs) like GPT-3 or GPT-4 at inference time to generate summaries directly; however,…