3 citations · 5 across the 6 of their papers we have counts for
7 papers
Making Sense of Animal-to-Human Drug Development Evidence: Stakeholder Practices, Challenges, and Requirements for AI Tools
Rosni Vasu, Simona E. Doneva, Benjamin V. Ineichen
Animal models are widely used to study human biology and health interventions, yet translating findings from animal studies to humans remains challenging. Evidence across preclinic…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
Jonathan Bragg, Mike D'Arcy, Nishant Balepur +36
AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions o…
HARPA: A Testability-Driven, Literature-Grounded Framework for Research Ideation
Rosni Vasu, Peter Jansen, Pao Siangliulue +4
While there has been a surge of interest in automated scientific discovery (ASD), especially with the emergence of LLMs, it remains challenging for tools to generate hypotheses tha…
HypER: Literature-grounded Hypothesis Generation and Distillation with Provenance
Rosni Vasu, Chandrayee Basu, Bhavana Dalvi Mishra +3
Large Language models have demonstrated promising performance in research ideation across scientific domains. Hypothesis development, the process of generating a highly specific de…
Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical Texts
Chandrayee Basu, Rosni Vasu, Michihiro Yasunaga +1
Automatic medical text simplification can assist providers with patient-friendly communication and make medical texts more accessible, thereby improving health literacy. But curati…
Gradient-based Data Subversion Attack Against Binary Classifiers
Rosni K Vasu, Sanjay Seetharaman, Shubham Malaviya +2
Machine learning based data-driven technologies have shown impressive performances in a variety of application domains. Most enterprises use data from multiple sources to provide q…
Influence Based Defense Against Data Poisoning Attacks in Online Learning
Sanjay Seetharaman, Shubham Malaviya, Rosni KV +2
Data poisoning is a type of adversarial attack on training data where an attacker manipulates a fraction of data to degrade the performance of machine learning model. Therefore, ap…