collaborators

6 papers

cs.AI2026

Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?

Spandan Garg, Vikram Nitin, Yufan Huang

Modern coding agents increasingly delegate specialized subtasks to subagents, which are smaller, focused agentic loops that handle narrow responsibilities like search, debugging or…

cs.SE2026

Code Quality Analysis of Translations from C to Rust

Biruk Tadesse, Vikram Nitin, Mazin Salah +3

C/C++ is a prevalent programming language. Yet, it suffers from significant memory and thread-safety issues. Recent studies have explored automated translation of C/C++ to safer la…

cs.SE2025

C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques

Vikram Nitin, Rahul Krishna, Luiz Lemos do Valle +1

In recent years, there has been a lot of interest in converting C code to Rust, to benefit from the memory and thread safety guarantees of Rust. C2Rust is a rule-based system that…

cs.SE2025

SpecTra: Enhancing the Code Translation Ability of Language Models by Generating Multi-Modal Specifications

Vikram Nitin, Rahul Krishna, Baishakhi Ray

Large language models (LLMs) are increasingly being used for the task of automated code translation, which has important real-world applications. However, most existing approaches…

cs.SE2025

FaultLine: Automated Proof-of-Vulnerability Generation Using LLM Agents

Vikram Nitin, Baishakhi Ray, Roshanak Zilouchian Moghaddam

Despite the critical threat posed by software security vulnerabilities, reports are often incomplete, lacking the proof-of-vulnerability (PoV) tests needed to validate fixes and pr…

cs.SE2025

Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language

Vikram Nitin, Anne Mulhern, Sanjay Arora +1

The Rust programming language is becoming increasingly popular among systems programmers due to its efficient performance and robust memory safety guarantees. Rust employs an owner…