4 citations · 8 across the 9 of their papers we have counts for
10 papers
Hierarchical Evaluation of Software Design Capabilities of Large Language Models of Code
Mootez Saad, Boqi Chen, José Antonio Hernández López +2
Large language models (LLMs) are being increasingly adopted in the software engineering domain, yet the robustness of their grasp on core software design concepts remains unclear.…
On the Effect of Token Merging on Pre-trained Models for Code
Mootez Saad, Hao Li, Tushar Sharma +1
Tokenization is a fundamental component of language models for code. It involves breaking down the input into units that are later passed to the language model stack to learn high-…
Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations
Saurabhsingh Rajput, Mootez Saad, Tushar Sharma
AI's exponential growth intensifies computational demands and energy challenges. While practitioners employ various optimization techniques, that we refer as "knobs" in this paper,…
SENAI: Towards Software Engineering Native Generative Artificial Intelligence
Mootez Saad, José Antonio Hernández López, Boqi Chen +3
Large Language Models have significantly advanced the field of code generation, demonstrating the ability to produce functionally correct code snippets. However, advancements in ge…
ALPINE: An adaptive language-agnostic pruning method for language models for code
Mootez Saad, José Antonio Hernández López, Boqi Chen +2
Language models of code have demonstrated state-of-the-art performance across various software engineering and source code analysis tasks. However, their demanding computational re…
CONCORD: Towards a DSL for Configurable Graph Code Representation
Mootez Saad, Tushar Sharma
Deep learning is widely used to uncover hidden patterns in large code corpora. To achieve this, constructing a format that captures the relevant characteristics and features of sou…
On Inter-dataset Code Duplication and Data Leakage in Large Language Models
José Antonio Hernández López, Boqi Chen, Mootez Saaz +2
Motivation. Large language models (LLMs) have exhibited remarkable proficiency in diverse software engineering (SE) tasks. Handling such tasks typically involves acquiring foundati…
Naturalness of Attention: Revisiting Attention in Code Language Models
Mootez Saad, Tushar Sharma
Language models for code such as CodeBERT offer the capability to learn advanced source code representation, but their opacity poses barriers to understanding of captured propertie…
DACOS-A Manually Annotated Dataset of Code Smells
Himesh Nandani, Mootez Saad, Tushar Sharma
Researchers apply machine-learning techniques for code smell detection to counter the subjectivity of many code smells. Such approaches need a large, manually annotated dataset for…
Adaptive Artificial Intelligent Q&A Platform
M. R, Akram, C. P +8
The paper presents an approach to build a question and answer system that is capable of processing the information in a large dataset and allows the user to gain knowledge from thi…