10 citations · 18 across the 9 of their papers we have counts for
9 papers
Compressing Long Context into Answer-Aligned Memory Embeddings for LLM Inference
Md Mostafizer Rahman, Md Faizul Ibne Amin, Md Shahajada Mia +2
Large language model (LLM) inference is constrained by the quadratic scaling of self-attention and the linear scaling of the KV cache, increasing latency, energy consumption, and G…
Revision-Aware Success Prediction from Multi-Attempt Programming Trajectories
Md Faizul Ibne Amin, Yutaka Watanobe, Daniel M. Muepu +4
Programming outcome prediction plays a central role in data-driven programming education, supporting learner modeling, timely intervention, and adaptive assistance. Yet predicting…
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…
Large Language Models for Education and Research: An Empirical and User Survey-based Analysis
Md Mostafizer Rahman, Ariful Islam Shiplu, Md Faizul Ibne Amin +2
Pretrained Large Language Models (LLMs) have achieved remarkable success across diverse domains, with education and research emerging as particularly impactful areas. Among current…
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…
Program Repair with Minimal Edits Using CodeT5
Atsushi Shirafuji, Md. Mostafizer Rahman, Md Faizul Ibne Amin +1
Programmers often struggle to identify and fix bugs in their programs. In recent years, many language models (LMs) have been proposed to fix erroneous programs and support error re…