39 citations · 116 across the 35 of their papers we have counts for
4 papers · 1 filter
Training Reasoning Models to Generate Diverse Scientific Ideas
Manya Wadhwa, Pranav Narayanan Venkit, Hiroaki Hayashi +3
One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of this work optimizes the qua…
Generative AI floods and dilutes the market for books
Tuhin Chakrabarty, Xinyue Liu, Jane C. Ginsburg +1
Generative AI can produce book-length works of fiction at near-zero cost. These books are often dismissed as low-quality ``slop'' that buyers will ignore, and are assumed to carry…
Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models
Xinyue Liu, Niloofar Mireshghallah, Jane C. Ginsburg +1
Frontier LLM companies have repeatedly assured courts and regulators that their models do not store copies of training data. They further rely on safety alignment strategies via RL…
Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books
Tuhin Chakrabarty, Paramveer S. Dhillon
Creative writing has long been considered a uniquely human endeavor, requiring voice and style that machines could not replicate. This assumption is challenged by Generative AI tha…