Image de couverture de livre

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Jin, Bihui, Wang, Jiayue, Nie, Pengyu
Format:	Preprint
Publié:	2025
Sujets:	Software Engineering Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility
par: Jin, Bihui, et autres
Publié: (2026)

TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
par: Li, Yinxi, et autres
Publié: (2025)

CodeJudge: Evaluating Code Generation with Large Language Models
par: Tong, Weixi, et autres
Publié: (2024)

Let the Code LLM Edit Itself When You Edit the Code
par: He, Zhenyu, et autres
Publié: (2024)

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
par: Jain, Naman, et autres
Publié: (2024)

Towards Understanding What Code Language Models Learned
par: Ahmed, Toufique, et autres
Publié: (2023)

Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning
par: Yang, Rem, et autres
Publié: (2025)

CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences
par: Weyssow, Martin, et autres
Publié: (2024)

ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning
par: Jiang, Juyong, et autres
Publié: (2026)

Evaluating Language Models for Efficient Code Generation
par: Liu, Jiawei, et autres
Publié: (2024)

Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation
par: Haider, Md. Asif, et autres
Publié: (2024)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
par: Weyssow, Martin, et autres
Publié: (2023)

TAROT: Test-driven and Capability-adaptive Curriculum Reinforcement Fine-tuning for Code Generation with Large Language Models
par: Park, Chansung, et autres
Publié: (2026)

GLLM: Self-Corrective G-Code Generation using Large Language Models with User Feedback
par: Abdelaal, Mohamed, et autres
Publié: (2025)

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
par: Guo, Daya, et autres
Publié: (2024)

Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study
par: Li, Yufei, et autres
Publié: (2024)

CODEMENV: Benchmarking Large Language Models on Code Migration
par: Cheng, Keyuan, et autres
Publié: (2025)

NExT: Teaching Large Language Models to Reason about Code Execution
par: Ni, Ansong, et autres
Publié: (2024)

Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
par: Cassano, Federico, et autres
Publié: (2023)

Evaluation and Improvement of Fault Detection for Large Language Models
par: Hu, Qiang, et autres
Publié: (2024)

CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation
par: Wang, Xinchen, et autres
Publié: (2025)

Can OpenSource beat ChatGPT? -- A Comparative Study of Large Language Models for Text-to-Code Generation
par: Mayer, Luis, et autres
Publié: (2024)

CodeEditorBench: Evaluating Code Editing Capability of Large Language Models
par: Guo, Jiawei, et autres
Publié: (2024)

IntentCoding: Amplifying User Intent in Code Generation
par: Fang, Zheng, et autres
Publié: (2026)

Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models
par: Riddell, Martin, et autres
Publié: (2024)

code_transformed: The Influence of Large Language Models on Code
par: Xu, Yuliang, et autres
Publié: (2025)

WebGen-R1: Incentivizing Large Language Models to Generate Functional and Aesthetic Websites with Reinforcement Learning
par: Jiang, Juyong, et autres
Publié: (2026)

Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
par: Lu, Ruofan, et autres
Publié: (2025)

Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search
par: Li, Haochen, et autres
Publié: (2024)

Investigating the Efficacy of Large Language Models for Code Clone Detection
par: Khajezade, Mohamad, et autres
Publié: (2024)

Analysing Python Machine Learning Notebooks with Moose
par: Mignard, Marius, et autres
Publié: (2025)

Learning Code Preference via Synthetic Evolution
par: Liu, Jiawei, et autres
Publié: (2024)

Neuron Patching: Semantic-based Neuron-level Language Model Repair for Code Generation
par: Gu, Jian, et autres
Publié: (2023)

Evaluating the Process Modeling Abilities of Large Language Models -- Preliminary Foundations and Results
par: Fettke, Peter, et autres
Publié: (2025)

OptLLM: Optimal Assignment of Queries to Large Language Models
par: Liu, Yueyue, et autres
Publié: (2024)

DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation
par: Li, Jinyang, et autres
Publié: (2025)

What can Large Language Models Capture about Code Functional Equivalence?
par: Maveli, Nickil, et autres
Publié: (2024)

Optimizing Case-Based Reasoning System for Functional Test Script Generation with Large Language Models
par: Guo, Siyuan, et autres
Publié: (2025)

SODBench: A Large Language Model Approach to Documenting Spreadsheet Operations
par: Indika, Amila, et autres
Publié: (2025)

Exploring Large Language Models for Translating Romanian Computational Problems into English
par: Dumitran, Adrian Marius, et autres
Publié: (2025)