166 citations · 587 across the 57 of their papers we have counts for
3 papers · 1 filter
Lemur: Integrating Large Language Models in Automated Program Verification
Haoze Wu, Clark Barrett, Nina Narodytska
The demonstrated code-understanding capability of LLMs raises the question of whether they can be used for automated program verification, a task that demands high-level abstract r…
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems
Sagar Patel, Sangeetha Abdu Jyothi, Nina Narodytska
We present CrystalBox, a novel, model-agnostic, posthoc explainability framework for Deep Reinforcement Learning (DRL) controllers in the large family of input-driven environments…
Plume: A Framework for High Performance Deep RL Network Controllers via Prioritized Trace Sampling
Sagar Patel, Junyang Zhang, Sangeetha Abdu Jyothi +1
Deep Reinforcement Learning (DRL) has shown promise in various networking environments. However, these environments present several fundamental challenges for standard DRL techniqu…