CodeGrad: Integrating Multi-Step Verification with Gradient-Based LLM Refinement
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Yueke, Zhang, Yifan, Leach, Kevin, Huang, Yu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DPO-F+: Aligning Code Repair Feedback with Developers' Preferences
by: Fang, Zihan, et al.
Published: (2025)
by: Fang, Zihan, et al.
Published: (2025)
Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery
by: Zhang, Yifan, et al.
Published: (2026)
by: Zhang, Yifan, et al.
Published: (2026)
Pre-Training Representations of Binary Code Using Contrastive Learning
by: Zhang, Yifan, et al.
Published: (2022)
by: Zhang, Yifan, et al.
Published: (2022)
EyeLayer: Integrating Human Attention Patterns into LLM-Based Code Summarization
by: Zhang, Jiahao, et al.
Published: (2026)
by: Zhang, Jiahao, et al.
Published: (2026)
Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation
by: Acharya, Manish, et al.
Published: (2025)
by: Acharya, Manish, et al.
Published: (2025)
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
by: Zhang, Yifan, et al.
Published: (2025)
by: Zhang, Yifan, et al.
Published: (2025)
SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair
by: Zhang, Yifan, et al.
Published: (2026)
by: Zhang, Yifan, et al.
Published: (2026)
K-ASTRO: Structure-Aware Adaptation of LLMs for Code Vulnerability Detection
by: Zhang, Yifan, et al.
Published: (2022)
by: Zhang, Yifan, et al.
Published: (2022)
Enhancing Code LLM Training with Programmer Attention
by: Zhang, Yifan, et al.
Published: (2025)
by: Zhang, Yifan, et al.
Published: (2025)
Do Machines and Humans Focus on Similar Code? Exploring Explainability of Large Language Models in Code Summarization
by: Li, Jiliang, et al.
Published: (2024)
by: Li, Jiliang, et al.
Published: (2024)
Context-Guided Decompilation: A Step Towards Re-executability
by: Wang, Xiaohan, et al.
Published: (2025)
by: Wang, Xiaohan, et al.
Published: (2025)
Integrated Modeling, Verification, and Code Generation for Unmanned Aerial Systems
by: Zhang, Jianyu, et al.
Published: (2024)
by: Zhang, Jianyu, et al.
Published: (2024)
LLM-Assisted Tool for Joint Generation of Formulas and Functions in Rule-Based Verification of Map Transformations
by: He, Ruidi, et al.
Published: (2025)
by: He, Ruidi, et al.
Published: (2025)
COMCAT: Leveraging Human Judgment to Improve Automatic Documentation and Summarization
by: Grandel, Skyler, et al.
Published: (2024)
by: Grandel, Skyler, et al.
Published: (2024)
CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation
by: Pan, Ruwei, et al.
Published: (2025)
by: Pan, Ruwei, et al.
Published: (2025)
Demystifying Faulty Code with LLM: Step-by-Step Reasoning for Explainable Fault Localization
by: Widyasari, Ratnadira, et al.
Published: (2024)
by: Widyasari, Ratnadira, et al.
Published: (2024)
LLM-Based Static Verification of Code Against Natural-Language Requirements: An Industrial Experience Report
by: Zhou, Zhi Quan, et al.
Published: (2026)
by: Zhou, Zhi Quan, et al.
Published: (2026)
SpecSyn: LLM-based Synthesis and Refinement of Formal Specifications for Real-world Program Verification
by: Ma, Lezhi, et al.
Published: (2026)
by: Ma, Lezhi, et al.
Published: (2026)
TRACE: Evaluating Execution Efficiency of LLM-Based Code Translation
by: Gong, Zhihao, et al.
Published: (2025)
by: Gong, Zhihao, et al.
Published: (2025)
TRACE: Evaluating Execution Efficiency of LLM-Based Code Translation
by: Gong, Zhihao, et al.
Published: (2026)
by: Gong, Zhihao, et al.
Published: (2026)
Whose fault is it anyway? SILC: Safe Integration of LLM-Generated Code
by: Lin, Peisen, et al.
Published: (2024)
by: Lin, Peisen, 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)
Inducing Vulnerable Code Generation in LLM Coding Assistants
by: Zeng, Binqi, et al.
Published: (2025)
by: Zeng, Binqi, et al.
Published: (2025)
Quantum-Guided Test Case Minimization for LLM-Based Code Generation
by: Zhang, Huixiang, et al.
Published: (2025)
by: Zhang, Huixiang, et al.
Published: (2025)
Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
by: He, Lehan, et al.
Published: (2025)
by: He, Lehan, et al.
Published: (2025)
Decoding Human-LLM Collaboration in Coding: An Empirical Study of Multi-Turn Conversations in the Wild
by: Zhang, Binquan, et al.
Published: (2025)
by: Zhang, Binquan, et al.
Published: (2025)
MACAA: Belief-Revision Multi-Agent Reasoning for Code Authorship Verification
by: Ye, Jingwei, et al.
Published: (2026)
by: Ye, Jingwei, et al.
Published: (2026)
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
by: Zheng, Tianyu, et al.
Published: (2024)
by: Zheng, Tianyu, et al.
Published: (2024)
Completion by Comprehension: Guiding Code Generation with Multi-Granularity Understanding
by: Zhao, Xinkui, et al.
Published: (2025)
by: Zhao, Xinkui, et al.
Published: (2025)
Structural Abstraction and Selective Refinement for Formal Verification
by: Luckeneder, Christoph, et al.
Published: (2025)
by: Luckeneder, Christoph, et al.
Published: (2025)
Stitch: Step-by-step LLM Guided Tutoring for Scratch
by: Si, Yuan, et al.
Published: (2025)
by: Si, Yuan, et al.
Published: (2025)
LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review
by: Rasheeda, Zeeshan, et al.
Published: (2026)
by: Rasheeda, Zeeshan, et al.
Published: (2026)
An Empirical Study of Interaction Smells in Multi-Turn Human-LLM Collaborative Code Generation
by: Zhang, Binquan, et al.
Published: (2026)
by: Zhang, Binquan, et al.
Published: (2026)
AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length
by: Cheng, Junhang, et al.
Published: (2025)
by: Cheng, Junhang, et al.
Published: (2025)
A Vulnerability Code Intent Summary Dataset
by: Huang, Yifan, et al.
Published: (2025)
by: Huang, Yifan, et al.
Published: (2025)
Condor: A Code Discriminator Integrating General Semantics with Code Details
by: Liang, Qingyuan, et al.
Published: (2024)
by: Liang, Qingyuan, et al.
Published: (2024)
SemOpt: LLM-Driven Code Optimization via Rule-Based Analysis
by: Zhao, Yuwei, et al.
Published: (2025)
by: Zhao, Yuwei, et al.
Published: (2025)
Verification Limits Code LLM Training
by: Gureja, Srishti, et al.
Published: (2025)
by: Gureja, Srishti, et al.
Published: (2025)
MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution
by: Wang, Yibo, et al.
Published: (2025)
by: Wang, Yibo, et al.
Published: (2025)
Benchmarking and Studying the LLM-based Code Review
by: Zeng, Zhengran, et al.
Published: (2025)
by: Zeng, Zhengran, et al.
Published: (2025)
Similar Items
-
DPO-F+: Aligning Code Repair Feedback with Developers' Preferences
by: Fang, Zihan, et al.
Published: (2025) -
Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery
by: Zhang, Yifan, et al.
Published: (2026) -
Pre-Training Representations of Binary Code Using Contrastive Learning
by: Zhang, Yifan, et al.
Published: (2022) -
EyeLayer: Integrating Human Attention Patterns into LLM-Based Code Summarization
by: Zhang, Jiahao, et al.
Published: (2026) -
Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation
by: Acharya, Manish, et al.
Published: (2025)