563 citations · 655 across the 15 of their papers we have counts for
3 papers · 1 filter
Revisiting Generalization Across Difficulty Levels: It's Not So Easy
Yeganeh Kordi, Nihal V. Nayak, Max Zuo +2
We investigate how well large language models (LLMs) generalize across different task difficulties, a key question for effective data curation and evaluation. Existing research is…
Boomerang Distillation Enables Zero-Shot Model Size Interpolation
Sara Kangaslahti, Nihal V. Nayak, Jonathan Geuter +3
Large language models (LLMs) are typically deployed under diverse memory and compute constraints. Existing approaches build model families by training each size independently, whic…
K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction
Tassallah Abdullahi, Ioanna Gemou, Nihal V. Nayak +4
Biomedical knowledge graphs (KGs) encode rich, structured information critical for drug discovery tasks, but extracting meaningful insights from large-scale KGs remains challenging…