4 citations · 6 across the 15 of their papers we have counts for
15 papers
Benchmarking and Enhancing Text-to-Image Models for Generating Visual Representations in Early Arithmetic Education
Junling Wang, Boqi Chen, Heejin Do +3
AI systems are increasingly used to support educational content creation, yet it remains unclear whether they can generate outputs that faithfully represent the pedagogical concept…
Projectional Decoding: Towards Semantic-Aware LLM Generation
Boqi Chen, José Antonio Hernández López, Aren A. Babikian
Large language models (LLMs) are increasingly used to generate software artifacts across many software engineering (SE) tasks, yet ensuring the semantic validity of these artifacts…
LLM-Assisted Repository-Level Generation with Structured Spec-Driven Engineering
Shuzhao Feng, Boqi Chen, Brett H Meyer +1
State-of-the-art Large Language Models (LLMs) excel in code generation at the function level. However, the output quality significantly declines when scaling to repository-level sy…
Structure- and Event-Driven Frameworks for State Machine Modeling with Large Language Models
Samer Abdulkarim, Evan Boyd, Karl Bridi +3
UML state machine design is a critical process in software engineering. Traditionally, state machines are manually crafted by experienced engineers based on natural language requir…
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.…
MCeT: Behavioral Model Correctness Evaluation using Large Language Models
Khaled Ahmed, Jialing Song, Boqi Chen +2
Behavioral model diagrams, e.g., sequence diagrams, are an essential form of documentation that are typically designed by system engineers from requirements documentation, either f…
SHERPA: A Model-Driven Framework for Large Language Model Execution
Boqi Chen, Kua Chen, José Antonio Hernández López +3
Recently, large language models (LLMs) have achieved widespread application across various fields. Despite their impressive capabilities, LLMs suffer from a lack of structured reas…
Accurate and Consistent Graph Model Generation from Text with Large Language Models
Boqi Chen, Ou Wei, Bingzhou Zheng +1
Graph model generation from natural language description is an important task with many applications in software engineering. With the rise of large language models (LLMs), there i…
LLM-based Satisfiability Checking of String Requirements by Consistent Data and Checker Generation
Boqi Chen, Aren A. Babikian, Shuzhao Feng +2
Requirements over strings, commonly represented using natural language (NL), are particularly relevant for software systems due to their heavy reliance on string data manipulation.…
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…
The Power of Types: Exploring the Impact of Type Checking on Neural Bug Detection in Dynamically Typed Languages
Boqi Chen, José Antonio Hernández López, Gunter Mussbacher +1
Motivation: Automated bug detection in dynamically typed languages such as Python is essential for maintaining code quality. The lack of mandatory type annotations in such language…
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…
Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
Boqi Chen, Kristóf Marussy, Oszkár Semeráth +2
Graph convolutional neural networks (GCNs) are powerful tools for learning graph-based knowledge representations from training data. However, they are vulnerable to small perturbat…
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…
Prompting or Fine-tuning? A Comparative Study of Large Language Models for Taxonomy Construction
Boqi Chen, Fandi Yi, Dániel Varró
Taxonomies represent hierarchical relations between entities, frequently applied in various software modeling and natural language processing (NLP) activities. They are typically s…