Cover Image

ACECode: A Reinforcement Learning Framework for Aligning Code Efficiency and Correctness in Code Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Chengran, Kang, Hong Jin, Shi, Jieke, Lo, David
Format:	Preprint
Published:	2024
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Think Like Human Developers: Harnessing Community Knowledge for Structured Code Reasoning
by: Yang, Chengran, et al.
Published: (2025)

Greening Large Language Models of Code
by: Shi, Jieke, et al.
Published: (2023)

Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)

Compiling Code LLMs into Lightweight Executables
by: Shi, Jieke, et al.
Published: (2026)

Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
by: Shi, Jieke, et al.
Published: (2024)

Unveiling Memorization in Code Models
by: Yang, Zhou, et al.
Published: (2023)

Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models
by: Yang, Zhou, et al.
Published: (2023)

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation
by: Hu, Li, et al.
Published: (2026)

Hotfixing Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)

Token Sugar: Making Source Code Sweeter for LLMs through Token-Efficient Shorthand
by: Sun, Zhensu, et al.
Published: (2025)

Curiosity-Driven Testing for Sequential Decision-Making Process
by: He, Junda, et al.
Published: (2025)

AgentSZZ: Teaching the LLM Agent to Play Detective with Bug-Inducing Commits
by: Lyu, Yunbo, et al.
Published: (2026)

Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)

Semantics-Aligned, Curriculum-Driven, and Reasoning-Enhanced Vulnerability Repair Framework
by: Yang, Chengran, et al.
Published: (2025)

From Code to Courtroom: LLMs as the New Software Judges
by: He, Junda, et al.
Published: (2025)

Human-Aligned Code Readability Assessment with Large Language Models
by: Ouédraogo, Wendkûuni C., et al.
Published: (2025)

Bridging Developer Instructions and Code Completion Through Instruction-Aware Fill-in-the-Middle Paradigm
by: Sun, Zhensu, et al.
Published: (2025)

"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistants
by: Lyu, Yunbo, et al.
Published: (2025)

CodeDPO: Aligning Code Models with Self Generated and Verified Source Code
by: Zhang, Kechi, et al.
Published: (2024)

PenForge: On-the-Fly Expert Agent Construction for Automated Penetration Testing
by: Huang, Huihui, et al.
Published: (2026)

Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
by: Shi, Jieke, et al.
Published: (2024)

Mut4All: Fuzzing Compilers via LLM-Synthesized Mutators Learned from Bug Reports
by: Wang, Bo, et al.
Published: (2025)

TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning
by: Wang, Guoqing, et al.
Published: (2026)

APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation
by: Yang, Chengran, et al.
Published: (2023)

Benchmarking Large Language Models for Multi-Language Software Vulnerability Detection
by: Zhang, Ting, et al.
Published: (2025)

An Execution-Verified Multi-Language Benchmark for Code Semantic Reasoning
by: Li, Yikun, et al.
Published: (2026)

Aligning Requirement for Large Language Model's Code Generation
by: Tian, Zhao, et al.
Published: (2025)

Autoregressive, Yet Revisable: In Decoding Revision for Secure Code Generation
by: Yang, Chengran, et al.
Published: (2026)

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding
by: Shi, Yuling, et al.
Published: (2026)

ESG Reporting Lifecycle Management with Large Language Models and AI Agents
by: Hoang, Thong, et al.
Published: (2026)

Executing as You Generate: Hiding Execution Latency in LLM Code Generation
by: Sun, Zhensu, et al.
Published: (2026)

Towards Better Correctness and Efficiency in Code Generation
by: Feng, Yunlong, et al.
Published: (2025)

SecureVibeBench: Benchmarking Secure Vibe Coding of AI Agents via Reconstructing Vulnerability-Introducing Scenarios
by: Chen, Junkai, et al.
Published: (2025)

Calibration and Correctness of Language Models for Code
by: Spiess, Claudio, et al.
Published: (2024)

Learning to Align Human Code Preferences
by: Yin, Xin, et al.
Published: (2025)

Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis
by: Huang, Huihui, et al.
Published: (2026)

Mercury: A Code Efficiency Benchmark for Code Large Language Models
by: Du, Mingzhe, et al.
Published: (2024)

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning
by: Wang, Hao, et al.
Published: (2026)

UniCoR: Modality Collaboration for Robust Cross-Language Hybrid Code Retrieval
by: Yang, Yang, et al.
Published: (2025)

Adversarial Attacks on Code Models with Discriminative Graph Patterns
by: Nguyen, Thanh-Dat, et al.
Published: (2023)