10 citations · 18 across the 9 of their papers we have counts for
5 papers · 1 filter
LLM-as-a-Judge for Contest-Style Human-AI Co-Creation: A Reliability-Aware Evaluation Framework for Coding
Md Faizul Ibne Amin, Yutaka Watanobe, Daniel M. Muepu +3
Large language models now judge open-ended outputs and co-create code with programmers, yet judgments of human-AI co-creation must be reliable, comparable across models, and interp…
CodeT5-RNN: Reinforcing Contextual Embeddings for Enhanced Code Comprehension
Md Mostafizer Rahman, Ariful Islam Shiplu, Yutaka Watanobe +3
Contextual embeddings generated by LLMs exhibit strong positional inductive biases, which can limit their ability to fully capture long-range, order-sensitive dependencies in highl…
Error Understanding in Program Code: A Systematic Study of LLM-DL Combinations for Multi-label Classification
Md Faizul Ibne Amin, Yutaka Watanobe, Md. Mostafizer Rahman +2
Programming is a core skill in CS and SE, yet identifying and resolving code errors remains challenging for practitioners. LLMs have shown remarkable capabilities in NL understandi…
Code Refactoring with LLM: A Comprehensive Evaluation With Few-Shot Settings
Md. Raihan Tapader, Md. Mostafizer Rahman, Ariful Islam Shiplu +2
In today's world, the focus of programmers has shifted from writing complex, error-prone code to prioritizing simple, clear, efficient, and sustainable code that makes programs eas…
Rule-Based Error Classification for Analyzing Differences in Frequent Errors
Atsushi Shirafuji, Taku Matsumoto, Md Faizul Ibne Amin +1
Finding and fixing errors is a time-consuming task not only for novice programmers but also for expert programmers. Prior work has identified frequent error patterns among various…