Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Zhou, Sun, Zhensu, Yue, Terry Zhuo, Devanbu, Premkumar, Lo, David |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Calibration of Large Language Models on Code Summarization
by: Virk, Yuvraj, et al.
Published: (2024)
by: Virk, Yuvraj, et al.
Published: (2024)
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)
by: Ahmed, Toufique, et al.
Published: (2023)
by: Ahmed, Toufique, et al.
Published: (2023)
CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance
by: Pai, Kunal, et al.
Published: (2025)
by: Pai, Kunal, et al.
Published: (2025)
Hotfixing Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Localized Calibrated Uncertainty in Code Language Models
by: Gros, David, et al.
Published: (2025)
by: Gros, David, et al.
Published: (2025)
Token Sugar: Making Source Code Sweeter for LLMs through Token-Efficient Shorthand
by: Sun, Zhensu, et al.
Published: (2025)
by: Sun, Zhensu, et al.
Published: (2025)
ICE-Score: Instructing Large Language Models to Evaluate Code
by: Zhuo, Terry Yue
Published: (2023)
by: Zhuo, Terry Yue
Published: (2023)
AI Coders Are Among Us: Rethinking Programming Language Grammar Towards Efficient Code Generation
by: Sun, Zhensu, et al.
Published: (2024)
by: Sun, Zhensu, 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)
Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy
by: Hussain, Aftab, et al.
Published: (2024)
by: Hussain, Aftab, et al.
Published: (2024)
RepairAgent: An Autonomous, LLM-Based Agent for Program Repair
by: Bouzenia, Islem, et al.
Published: (2024)
by: Bouzenia, Islem, et al.
Published: (2024)
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)
Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss
by: Yang, Guang, et al.
Published: (2024)
by: Yang, Guang, et al.
Published: (2024)
Autoregressive, Yet Revisable: In Decoding Revision for Secure Code Generation
by: Yang, Chengran, et al.
Published: (2026)
by: Yang, Chengran, et al.
Published: (2026)
Bridging Developer Instructions and Code Completion Through Instruction-Aware Fill-in-the-Middle Paradigm
by: Sun, Zhensu, et al.
Published: (2025)
by: Sun, Zhensu, et al.
Published: (2025)
The Hidden Cost of Readability: How Code Formatting Silently Consumes Your LLM Budget
by: Pan, Dangfeng, et al.
Published: (2025)
by: Pan, Dangfeng, et al.
Published: (2025)
Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
by: Yang, Guang, et al.
Published: (2023)
by: Yang, Guang, et al.
Published: (2023)
Studying LLM Performance on Closed- and Open-source Data
by: Ahmed, Toufique, et al.
Published: (2024)
by: Ahmed, Toufique, et al.
Published: (2024)
CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding
by: Shi, Yuling, et al.
Published: (2026)
by: Shi, Yuling, et al.
Published: (2026)
Greening Large Language Models of Code
by: Shi, Jieke, et al.
Published: (2023)
by: Shi, Jieke, et al.
Published: (2023)
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)
FDI: Attack Neural Code Generation Systems through User Feedback Channel
by: Sun, Zhensu, et al.
Published: (2024)
by: Sun, Zhensu, et al.
Published: (2024)
Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems
by: Sun, Zhensu, et al.
Published: (2022)
by: Sun, Zhensu, et al.
Published: (2022)
From Code to Courtroom: LLMs as the New Software Judges
by: He, Junda, et al.
Published: (2025)
by: He, Junda, et al.
Published: (2025)
Executing as You Generate: Hiding Execution Latency in LLM Code Generation
by: Sun, Zhensu, et al.
Published: (2026)
by: Sun, Zhensu, et al.
Published: (2026)
Less is More: DocString Compression in Code Generation
by: Yang, Guang, et al.
Published: (2024)
by: Yang, Guang, et al.
Published: (2024)
Less is More: Towards Green Code Large Language Models via Unified Structural Pruning
by: Yang, Guang, et al.
Published: (2024)
by: Yang, Guang, et al.
Published: (2024)
Can LLMs Replace Manual Annotation of Software Engineering Artifacts?
by: Ahmed, Toufique, et al.
Published: (2024)
by: Ahmed, Toufique, 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)
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)
CFCEval: Evaluating Security Aspects in Code Generated by Large Language Models
by: Cheng, Cheng, et al.
Published: (2025)
by: Cheng, Cheng, et al.
Published: (2025)
When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference
by: Sun, Zhensu, et al.
Published: (2024)
by: Sun, Zhensu, et al.
Published: (2024)
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)
UniCoR: Modality Collaboration for Robust Cross-Language Hybrid Code Retrieval
by: Yang, Yang, et al.
Published: (2025)
by: Yang, Yang, et al.
Published: (2025)
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)
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)
Does In-IDE Calibration of Large Language Models work at Scale?
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
Calibration and Correctness of Language Models for Code
by: Spiess, Claudio, et al.
Published: (2024)
by: Spiess, Claudio, et al.
Published: (2024)
Usability as a Weapon: Attacking the Safety of LLM-Based Code Generation via Usability Requirements
by: Li, Yue, et al.
Published: (2026)
by: Li, Yue, et al.
Published: (2026)
Similar Items
-
Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024) -
Calibration of Large Language Models on Code Summarization
by: Virk, Yuvraj, et al.
Published: (2024) -
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)
by: Ahmed, Toufique, et al.
Published: (2023) -
CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance
by: Pai, Kunal, et al.
Published: (2025) -
Hotfixing Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)