24 citations · 41 across the 12 of their papers we have counts for
12 papers
Progressive Safeguards for Safe and Model-Agnostic Reinforcement Learning
Nabil Omi, Hosein Hasanbeig, Hiteshi Sharma +2
In this paper we propose a formal, model-agnostic meta-learning framework for safe reinforcement learning. Our framework is inspired by how parents safeguard their children across…
STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with FeedBack
Shashank Kirtania, Naman Gupta, Priyanshu Gupta +7
Large Language Models (LLMs) often generate incorrect or outdated information, especially in low-resource settings or when dealing with private data. To address this, Retrieval-Aug…
Frustrated with Code Quality Issues? LLMs can Help!
Nalin Wadhwa, Jui Pradhan, Atharv Sonwane +5
As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis to…
CodePlan: Repository-level Coding using LLMs and Planning
Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade +6
Software engineering activities such as package migration, fixing errors reports from static analysis or testing, and adding type annotations or other specifications to a codebase,…
PwR: Exploring the Role of Representations in Conversational Programming
Pradyumna YM, Vinod Ganesan, Dinesh Kumar Arumugam +7
Large Language Models (LLMs) have revolutionized programming and software engineering. AI programming assistants such as GitHub Copilot X enable conversational programming, narrowi…
StaticFixer: From Static Analysis to Static Repair
Naman Jain, Shubham Gandhi, Atharv Sonwane +5
Static analysis tools are traditionally used to detect and flag programs that violate properties. We show that static analysis tools can also be used to perturb programs that satis…