4 papers
CreativeInstruct: Scalably Teaching LLMs to Balance Quality, Creativity, and Diversity
Ananya Sahu, Mohit Bansal, Elias Stengel-Eskin
While post-training improves the capabilities of large language models (LLMs), it generally lowers their output diversity and creativity, negatively impacting tasks that explicitly…
The Culture Funnel: You Can't Align What isn't in the Data
Ananya Sahu, Mehrnaz Mofakhami, Daniel D'Souza +3
Current cultural alignment approaches focus on inference-time interventions, assuming models already contain sufficient cultural knowledge. We argue modern LLM pipelines suffer fro…
Tiny Aya: Bridging Scale and Multilingual Depth
Alejandro R. Salamanca, Diana Abagyan, Daniel D'souza +23
Tiny Aya redefines what a small multilingual language model can achieve. Trained on 70 languages and refined through region-aware posttraining, it delivers state-of-the-art in tran…
Mining Contextualized Visual Associations from Images for Creativity Understanding
Ananya Sahu, Amith Ananthram, Kathleen McKeown
Understanding another person's creative output requires a shared language of association. However, when training vision-language models such as CLIP, we rely on web-scraped dataset…