Do Large Language Models Pay Similar Attention Like Human Programmers When Generating Code?
Fuente:
arXiv
Saved in:
| Main Authors: | Kou, Bonan, Chen, Shengmai, Wang, Zhijie, Ma, Lei, Zhang, Tianyi |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Evaluating the Quality of Code Comments Generated by Large Language Models for Novice Programmers
by: Fan, Aysa Xuemo, et al.
Published: (2024)
by: Fan, Aysa Xuemo, et al.
Published: (2024)
Enhancing Code LLM Training with Programmer Attention
by: Zhang, Yifan, et al.
Published: (2025)
by: Zhang, Yifan, et al.
Published: (2025)
Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
by: Wang, Zhijie, et al.
Published: (2024)
by: Wang, Zhijie, et al.
Published: (2024)
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
by: Mozannar, Hussein, et al.
Published: (2024)
by: Mozannar, Hussein, et al.
Published: (2024)
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
by: Zhang, Yifan, et al.
Published: (2025)
by: Zhang, Yifan, et al.
Published: (2025)
"Always Nice and Confident, Sometimes Wrong": Developer's Experiences Engaging Large Language Models (LLMs) Versus Human-Powered Q&A Platforms for Coding Support
by: Li, Jiachen, et al.
Published: (2023)
by: Li, Jiachen, et al.
Published: (2023)
SPROUT: an Interactive Authoring Tool for Generating Programming Tutorials with the Visualization of Large Language Models
by: Liu, Yihan, et al.
Published: (2023)
by: Liu, Yihan, et al.
Published: (2023)
In-IDE Human-AI Experience in the Era of Large Language Models; A Literature Review
by: Sergeyuk, Agnia, et al.
Published: (2024)
by: Sergeyuk, Agnia, et al.
Published: (2024)
Evolution of Programmers' Trust in Generative AI Programming Assistants
by: Shah, Anshul, et al.
Published: (2025)
by: Shah, Anshul, et al.
Published: (2025)
Generating Complex Code Analyzers from Natural Language Questions
by: Nazari, Amirmohammad, et al.
Published: (2026)
by: Nazari, Amirmohammad, et al.
Published: (2026)
Reassessing Java Code Readability Models with a Human-Centered Approach
by: Sergeyuk, Agnia, et al.
Published: (2024)
by: Sergeyuk, Agnia, et al.
Published: (2024)
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization
by: Zhang, Yifan, et al.
Published: (2024)
by: Zhang, Yifan, et al.
Published: (2024)
UICoder: Finetuning Large Language Models to Generate User Interface Code through Automated Feedback
by: Wu, Jason, et al.
Published: (2024)
by: Wu, Jason, et al.
Published: (2024)
Recommending Usability Improvements with Multimodal Large Language Models
by: Lubos, Sebastian, et al.
Published: (2026)
by: Lubos, Sebastian, et al.
Published: (2026)
How Scientists Use Large Language Models to Program
by: O'Brien, Gabrielle
Published: (2025)
by: O'Brien, Gabrielle
Published: (2025)
Bridging the Interpretation Gap in Accessibility Testing: Empathetic and Legal-Aware Bug Report Generation via Large Language Models
by: Koyama, Ryoya, et al.
Published: (2026)
by: Koyama, Ryoya, et al.
Published: (2026)
Linguistic Similarity Within Centralized FLOSS Development
by: Gaughan, Matthew, et al.
Published: (2026)
by: Gaughan, Matthew, et al.
Published: (2026)
Large Language Models as Visualization Agents for Immersive Binary Reverse Engineering
by: Brown, Dennis, et al.
Published: (2025)
by: Brown, Dennis, et al.
Published: (2025)
Usability Analysis of Configurator User Interfaces with Multimodal Large Language Models
by: Lubos, Sebastian, et al.
Published: (2026)
by: Lubos, Sebastian, et al.
Published: (2026)
"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code
by: Zi, Yangtian, et al.
Published: (2025)
by: Zi, Yangtian, et al.
Published: (2025)
Accodemy: AI Powered Code Learning Platform to Assist Novice Programmers in Overcoming the Fear of Coding
by: Aamina, M. A. F., et al.
Published: (2025)
by: Aamina, M. A. F., et al.
Published: (2025)
Investigating and Designing for Trust in AI-powered Code Generation Tools
by: Wang, Ruotong, et al.
Published: (2023)
by: Wang, Ruotong, et al.
Published: (2023)
Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions
by: Schön, David, et al.
Published: (2026)
by: Schön, David, et al.
Published: (2026)
What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI
by: Choudhuri, Rudrajit, et al.
Published: (2025)
by: Choudhuri, Rudrajit, et al.
Published: (2025)
Inferring Alt-text For UI Icons With Large Language Models During App Development
by: Haque, Sabrina, et al.
Published: (2024)
by: Haque, Sabrina, et al.
Published: (2024)
Dynamic Code Orchestration: Harnessing the Power of Large Language Models for Adaptive Script Execution
by: Del Vecchio, Justin, et al.
Published: (2024)
by: Del Vecchio, Justin, et al.
Published: (2024)
A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions
by: Tang, Ningzhi, et al.
Published: (2024)
by: Tang, Ningzhi, et al.
Published: (2024)
Digital Wellbeing Redefined: Toward User-Centric Approach for Positive Social Media Engagement
by: Zhao, Yixue, et al.
Published: (2024)
by: Zhao, Yixue, et al.
Published: (2024)
NaturalEdit: Code Modification through Direct Interaction with Adaptive Natural Language Representation
by: Tang, Ningzhi, et al.
Published: (2025)
by: Tang, Ningzhi, et al.
Published: (2025)
How Do Developers Interact with AI? An Exploratory Study on Modeling Developer Programming Behavior
by: Wu, Yinan, et al.
Published: (2026)
by: Wu, Yinan, et al.
Published: (2026)
Do I Belong? Modeling Sense of Virtual Community Among Linux Kernel Contributors
by: Trinkenreich, Bianca, et al.
Published: (2023)
by: Trinkenreich, Bianca, et al.
Published: (2023)
CodeAlignBench: Assessing Code Generation Models on Developer-Preferred Code Adjustments
by: Mehralian, Forough, et al.
Published: (2025)
by: Mehralian, Forough, et al.
Published: (2025)
An Exploratory Study on Upper-Level Computing Students' Use of Large Language Models as Tools in a Semester-Long Project
by: Tanay, Ben Arie, et al.
Published: (2024)
by: Tanay, Ben Arie, et al.
Published: (2024)
Exit the Code: A Model for Understanding Career Abandonment Intention Among Software Developers
by: Massoni, Tiago, et al.
Published: (2025)
by: Massoni, Tiago, et al.
Published: (2025)
Qualitative Coding Analysis through Open-Source Large Language Models: A User Study and Design Recommendations
by: Ngo, Tung T., et al.
Published: (2026)
by: Ngo, Tung T., et al.
Published: (2026)
Generative AI for CAD Automation: Leveraging Large Language Models for 3D Modelling
by: Kumar, Sumit, et al.
Published: (2025)
by: Kumar, Sumit, et al.
Published: (2025)
CodeA11y: Making AI Coding Assistants Useful for Accessible Web Development
by: Mowar, Peya, et al.
Published: (2025)
by: Mowar, Peya, et al.
Published: (2025)
Understanding User Mental Models in AI-Driven Code Completion Tools: Insights from an Elicitation Study
by: Desolda, Giuseppe, et al.
Published: (2025)
by: Desolda, Giuseppe, et al.
Published: (2025)
Gendered Prompting and LLM Code Review: How Gender Cues in the Prompt Shape Code Quality and Evaluation
by: Janzen, Lynn, et al.
Published: (2026)
by: Janzen, Lynn, et al.
Published: (2026)
EngThrive: Make It Fast and Easy to Do Great Work
by: Houck, Brian, et al.
Published: (2026)
by: Houck, Brian, et al.
Published: (2026)
Similar Items
-
Evaluating the Quality of Code Comments Generated by Large Language Models for Novice Programmers
by: Fan, Aysa Xuemo, et al.
Published: (2024) -
Enhancing Code LLM Training with Programmer Attention
by: Zhang, Yifan, et al.
Published: (2025) -
Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
by: Wang, Zhijie, et al.
Published: (2024) -
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
by: Mozannar, Hussein, et al.
Published: (2024) -
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
by: Zhang, Yifan, et al.
Published: (2025)