4 papers
REFINEPPO: Learning Continuous Control Policies by Iterative Action Refinement
Sachini Weerasekara, Sagar Kamarthi, Jacqueline Isaacs
Deep reinforcement learning (DRL) has achieved strong performance across a wide range of continuous-control problems. These continuous-control policies, however, are often defined…
Conditional Cognitive Biases in LLMs: How Biased User Turns Modulate In-Context Reasoning
Sachini Weerasekara, Sagar Kamarthi, Jacqueline Isaacs
We present an evaluation of cognitive bias expression in state-of-the-art instruction-tuned LLMs under realistic multi-turn interaction settings. Our work introduces a novel three-…
Prototype Guided Post-pretraining for Single-Cell Representation Learning
Sachini Weerasekara, Natasha Darras, Sagar Kamarthi +2
Single-cell representation learning (SCRL) from gene expression data offers a way to uncover the complex regulatory logic underlying cellular function. Inspired by large language m…
Temporal Data Requirement for Predicting Unplanned Hospital Readmissions
Ramin Mohammadi, Vahab vahdat, Sarthak Jain +3
With the proliferation of Electronic Health Records (EHRs), a critical challenge in building predictive models is determining the optimal historical data time window to maximize ac…