Cover Image

Breaking Memorization Barriers in LLM Code Fine-Tuning via Information Bottleneck for Improved Generalization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Changsheng, Chen, Xin, Liu, Sijia, Ding, Ke
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GiFT: Gibbs Fine-Tuning for Code Generation
by: Li, Haochen, et al.
Published: (2025)

Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
by: Tsai, Yun-Da, et al.
Published: (2024)

Promise and Peril of Collaborative Code Generation Models: Balancing Effectiveness and Memorization
by: Chen, Zhi, et al.
Published: (2024)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
by: Weyssow, Martin, et al.
Published: (2023)

Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
by: J, Mathav Raj, et al.
Published: (2024)

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
by: DeepSeek-AI, et al.
Published: (2024)

Refining Joint Text and Source Code Embeddings for Retrieval Task with Parameter-Efficient Fine-Tuning
by: Galliamov, Karim, et al.
Published: (2024)

Code Roulette: How Prompt Variability Affects LLM Code Generation
by: Paleyes, Andrei, et al.
Published: (2025)

LLM Performance for Code Generation on Noisy Tasks
by: Sendyka, Radzim, et al.
Published: (2025)

QiMeng-PRepair: Precise Code Repair via Edit-Aware Reward Optimization
by: Ke, Changxin, et al.
Published: (2026)

Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
by: Chakrabarty, Sayak, et al.
Published: (2024)

The Larger the Better? Improved LLM Code-Generation via Budget Reallocation
by: Hassid, Michael, et al.
Published: (2024)

Unlock the Correlation between Supervised Fine-Tuning and Reinforcement Learning in Training Code Large Language Models
by: Chen, Jie, et al.
Published: (2024)

Leveraging LLMs for Legacy Code Modernization: Challenges and Opportunities for LLM-Generated Documentation
by: Diggs, Colin, et al.
Published: (2024)

Think Anywhere in Code Generation
by: Jiang, Xue, et al.
Published: (2026)

One Model, Many Skills: Parameter-Efficient Fine-Tuning for Multitask Code Analysis
by: Akli, Amal, et al.
Published: (2026)

Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
by: Ryan, Gabriel, et al.
Published: (2024)

Renaissance of Literate Programming in the Era of LLMs: Enhancing LLM-Based Code Generation in Large-Scale Projects
by: Zhang, Wuyang, et al.
Published: (2024)

FGIT: Fault-Guided Fine-Tuning for Code Generation
by: Fan, Lishui, et al.
Published: (2025)

RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
by: Silva, André, et al.
Published: (2023)

Keeping Code-Aware LLMs Fresh: Full Refresh, In-Context Deltas, and Incremental Fine-Tuning
by: Sharma, Pradeep Kumar, et al.
Published: (2025)

A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages
by: Joel, Sathvik, et al.
Published: (2024)

Evaluating Language Models for Efficient Code Generation
by: Liu, Jiawei, et al.
Published: (2024)

RocketPPA: Code-Level Power, Performance, and Area Prediction via LLM and Mixture of Experts
by: Abdollahi, Armin, et al.
Published: (2025)

QiMeng-MuPa: Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
by: Ke, Changxin, et al.
Published: (2025)

Enhancing LLM-Based Test Generation by Eliminating Covered Code
by: Xu, WeiZhe, et al.
Published: (2026)

Planning-Aware Code Infilling via Horizon-Length Prediction
by: Ding, Yifeng, et al.
Published: (2024)

On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code
by: Weyssow, Martin, et al.
Published: (2023)

ADReFT: Adaptive Decision Repair for Safe Autonomous Driving via Reinforcement Fine-Tuning
by: Cheng, Mingfei, et al.
Published: (2025)

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters
by: Zine, Nada, et al.
Published: (2026)

FROAV: A Framework for RAG Observation and Agent Verification -- Lowering the Barrier to LLM Agent Research
by: Lin, Tzu-Hsuan, et al.
Published: (2026)

Fault Localization via Fine-tuning Large Language Models with Mutation Generated Stack Traces
by: Jambigi, Neetha, et al.
Published: (2025)

An Initial Exploration of Contrastive Prompt Tuning to Generate Energy-Efficient Code
by: Weidmann, Sophie, et al.
Published: (2026)

SemRep: Generative Code Representation Learning with Code Transformations
by: Li, Weichen, et al.
Published: (2026)

DeputyDev -- AI Powered Developer Assistant: Breaking the Code Review Logjam through Contextual AI to Boost Developer Productivity
by: Khare, Vishal, et al.
Published: (2025)

Learning Code Preference via Synthetic Evolution
by: Liu, Jiawei, et al.
Published: (2024)

Leveraging Reviewer Experience in Code Review Comment Generation
by: Lin, Hong Yi, et al.
Published: (2024)

LEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models
by: Wang, Yan, et al.
Published: (2025)

LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
by: Liu, Kaibo, et al.
Published: (2024)

SelfCodeAlign: Self-Alignment for Code Generation
by: Wei, Yuxiang, et al.
Published: (2024)