3 citations · 3 across the 4 of their papers we have counts for
4 papers
BEAVER: An Efficient Deterministic LLM Verifier
Tarun Suresh, Nalin Wadhwa, Debangshu Banerjee +1
As large language models (LLMs) transition from research prototypes to production systems, practitioners often need reliable methods to verify model outputs and characterize tail r…
Code Researcher: Deep Research Agent for Large Systems Code and Commit History
Ramneet Singh, Sathvik Joel, Abhav Mehrotra +4
Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code remains underexplored. Due to the size and…
MASAI: Modular Architecture for Software-engineering AI Agents
Daman Arora, Atharv Sonwane, Nalin Wadhwa +5
A common method to solve complex problems in software engineering, is to divide the problem into multiple sub-problems. Inspired by this, we propose a Modular Architecture for Soft…
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…