Greening Large Language Models of Code
Fuente:
arXiv
Saved in:
| Main Authors: | Shi, Jieke, Yang, Zhou, Kang, Hong Jin, Xu, Bowen, He, Junda, Lo, David |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ACECode: A Reinforcement Learning Framework for Aligning Code Efficiency and Correctness in Code Language Models
by: Yang, Chengran, et al.
Published: (2024)
by: Yang, Chengran, et al.
Published: (2024)
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
by: Shi, Jieke, et al.
Published: (2024)
by: Shi, Jieke, et al.
Published: (2024)
Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
by: Shi, Jieke, et al.
Published: (2024)
by: Shi, Jieke, et al.
Published: (2024)
Curiosity-Driven Testing for Sequential Decision-Making Process
by: He, Junda, et al.
Published: (2025)
by: He, Junda, et al.
Published: (2025)
Finding Safety Violations of AI-Enabled Control Systems through the Lens of Synthesized Proxy Programs
by: Shi, Jieke, et al.
Published: (2024)
by: Shi, Jieke, et al.
Published: (2024)
Think Like Human Developers: Harnessing Community Knowledge for Structured Code Reasoning
by: Yang, Chengran, et al.
Published: (2025)
by: Yang, Chengran, et al.
Published: (2025)
Compiling Code LLMs into Lightweight Executables
by: Shi, Jieke, et al.
Published: (2026)
by: Shi, Jieke, et al.
Published: (2026)
Hotfixing Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
From Code to Courtroom: LLMs as the New Software Judges
by: He, Junda, et al.
Published: (2025)
by: He, Junda, et al.
Published: (2025)
Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation
by: Hu, Li, et al.
Published: (2026)
by: Hu, Li, et al.
Published: (2026)
AgentSZZ: Teaching the LLM Agent to Play Detective with Bug-Inducing Commits
by: Lyu, Yunbo, et al.
Published: (2026)
by: Lyu, Yunbo, et al.
Published: (2026)
Unveiling Memorization in Code Models
by: Yang, Zhou, et al.
Published: (2023)
by: Yang, Zhou, et al.
Published: (2023)
APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation
by: Yang, Chengran, et al.
Published: (2023)
by: Yang, Chengran, et al.
Published: (2023)
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models
by: Yang, Zhou, et al.
Published: (2023)
by: Yang, Zhou, et al.
Published: (2023)
ESG Reporting Lifecycle Management with Large Language Models and AI Agents
by: Hoang, Thong, et al.
Published: (2026)
by: Hoang, Thong, et al.
Published: (2026)
LLM-as-a-Judge for Software Engineering: Literature Review, Vision, and the Road Ahead
by: He, Junda, et al.
Published: (2025)
by: He, Junda, et al.
Published: (2025)
PTM4Tag+: Tag Recommendation of Stack Overflow Posts with Pre-trained Models
by: He, Junda, et al.
Published: (2024)
by: He, Junda, et al.
Published: (2024)
Assessing and Advancing Benchmarks for Evaluating Large Language Models in Software Engineering Tasks
by: Hu, Xing, et al.
Published: (2025)
by: Hu, Xing, et al.
Published: (2025)
Identifying and Mitigating API Misuse in Large Language Models
by: Zhuo, Terry Yue, et al.
Published: (2025)
by: Zhuo, Terry Yue, et al.
Published: (2025)
LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead
by: He, Junda, et al.
Published: (2024)
by: He, Junda, et al.
Published: (2024)
Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis
by: Huang, Huihui, et al.
Published: (2026)
by: Huang, Huihui, et al.
Published: (2026)
Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Representation Learning for Stack Overflow Posts: How Far are We?
by: He, Junda, et al.
Published: (2023)
by: He, Junda, et al.
Published: (2023)
"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistants
by: Lyu, Yunbo, et al.
Published: (2025)
by: Lyu, Yunbo, et al.
Published: (2025)
SLICEMATE: Accurate and Scalable Static Program Slicing via LLM-Powered Agents
by: Chang, Jianming, et al.
Published: (2025)
by: Chang, Jianming, et al.
Published: (2025)
PatchZero: Zero-Shot Automatic Patch Correctness Assessment
by: Zhou, Xin, et al.
Published: (2023)
by: Zhou, Xin, et al.
Published: (2023)
Large Language Model for Vulnerability Detection: Emerging Results and Future Directions
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
Human-Aligned Code Readability Assessment with Large Language Models
by: Ouédraogo, Wendkûuni C., et al.
Published: (2025)
by: Ouédraogo, Wendkûuni C., et al.
Published: (2025)
Benchmarking Large Language Models for Multi-Language Software Vulnerability Detection
by: Zhang, Ting, et al.
Published: (2025)
by: Zhang, Ting, et al.
Published: (2025)
A Functional Software Reference Architecture for LLM-Integrated Systems
by: Bucaioni, Alessio, et al.
Published: (2025)
by: Bucaioni, Alessio, et al.
Published: (2025)
Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead
by: Bucaioni, Alessio, et al.
Published: (2025)
by: Bucaioni, Alessio, et al.
Published: (2025)
V-GameGym: Visual Game Generation for Code Large Language Models
by: Zhang, Wei, et al.
Published: (2025)
by: Zhang, Wei, et al.
Published: (2025)
Is Quantization a Deal-breaker? Empirical Insights from Large Code Models
by: Afrin, Saima, et al.
Published: (2025)
by: Afrin, Saima, et al.
Published: (2025)
Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
Context-Enhanced Vulnerability Detection Based on Large Language Model
by: Yang, Yixin, et al.
Published: (2025)
by: Yang, Yixin, et al.
Published: (2025)
ExeCoder: Empowering Large Language Models with Executability Representation for Code Translation
by: He, Minghua, et al.
Published: (2025)
by: He, Minghua, et al.
Published: (2025)
Finding Missing Input Validation in TEEs via LLM-Assisted Symbolic Execution
by: Ma, Chengyan, et al.
Published: (2026)
by: Ma, Chengyan, et al.
Published: (2026)
How Quantization Impacts Privacy Risk on LLMs for Code?
by: Haque, Md Nazmul, et al.
Published: (2025)
by: Haque, Md Nazmul, et al.
Published: (2025)
Back to the Basics: Rethinking Issue-Commit Linking with LLM-Assisted Retrieval
by: Huang, Huihui, et al.
Published: (2025)
by: Huang, Huihui, et al.
Published: (2025)
Similar Items
-
ACECode: A Reinforcement Learning Framework for Aligning Code Efficiency and Correctness in Code Language Models
by: Yang, Chengran, et al.
Published: (2024) -
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
by: Shi, Jieke, et al.
Published: (2024) -
Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024) -
Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
by: Shi, Jieke, et al.
Published: (2024) -
Curiosity-Driven Testing for Sequential Decision-Making Process
by: He, Junda, et al.
Published: (2025)