Papers Code Completion
“Code Completion” 태그가 달린 논문 280편 · 필터 해제
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks
Addressing the challenge of effectively processing long contexts has become a critical issue for Large Language Models (LLMs). Two common strategies have emerged: 1) reducing the input length, such as retrieving relevant…
Code CompletionLong-Form Narrative SummarizationQuestion AnsweringRAG+1SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning
Code Large Language Models (Code LLMs) have excelled at tasks like code completion but often miss deeper semantics such as execution effects and dynamic states. This paper aims to bridge the gap between Code LLMs' relian…
Code CompletionCode GenerationHumanEvalProgram RepairR2C2-Coder: Enhancing and Benchmarking Real-world Repository-level Code Completion Abilities of Code Large Language Models
Code completion models have made significant progress in recent years. Recently, repository-level code completion has drawn more attention in modern software development, and several baseline methods and benchmarks have …
BenchmarkingCode CompletionRetrievalDataflow-Guided Retrieval Augmentation for Repository-Level Code Completion
Recent years have witnessed the deployment of code language models (LMs) in various code intelligence tasks such as code completion. Yet, it is challenging for pre-trained LMs to generate correct completions in private r…
Code CompletionRetrievaltext similaritySuperposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass
Many applications today provide users with multiple auto-complete drafts as they type, including GitHub's code completion, Gmail's smart compose, and Apple's messaging auto-suggestions. Under the hood, language models su…
Code CompletionLanguage ModelingLanguage ModellingOptimizing Large Language Models for OpenAPI Code Completion
Recent advancements in Large Language Models (LLMs) and their utilization in code generation tasks have significantly reshaped the field of software development. Despite the remarkable efficacy of code completion solutio…
Code CompletionCode GenerationOpenAPI code completionPrompt EngineeringModel Cascading for Code: A Cascaded Black-Box Multi-Model Framework for Cost-Efficient Code Completion with Self-Testing
The rapid advancement of large language models (LLMs) has significantly improved code completion tasks, yet the trade-off between accuracy and computational cost remains a critical challenge. While using larger models an…
Code CompletionCode GenerationmodelText GenerationA Transformer-Based Approach for Smart Invocation of Automatic Code Completion
Transformer-based language models are highly effective for code completion, with much research dedicated to enhancing the content of these completions. Despite their effectiveness, these models come with high operational…
Code CompletionAutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}
We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo (April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test ($\mathbf{90.9\%}$ vs. $\mathbf{90.2\%}$). In addition, AutoCoder offers a …
Class-level Code GenerationCode CompletionCode GenerationCode Repair+8Full Line Code Completion: Bringing AI to Desktop
In recent years, several industrial solutions for the problem of multi-token code completion appeared, each making a great advance in the area but mostly focusing on cloud-based runtime and avoiding working on the end us…
Code CompletionDoes Your Neural Code Completion Model Use My Code? A Membership Inference Approach
Recent years have witnessed significant progress in developing deep learning-based models for automated code completion. Although using source code in GitHub has been a common practice for training deep-learning-based mo…
Code CompletionMemorizationRethinking Software Engineering in the Foundation Model Era: From Task-Driven AI Copilots to Goal-Driven AI Pair Programmers
The advent of Foundation Models (FMs) and AI-powered copilots has transformed the landscape of software development, offering unprecedented code completion capabilities and enhancing developer productivity. However, the …
Code CompletionDecision MakingSelf-LearningIs Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension
Large language models (LLMs) has experienced exponential growth, they demonstrate remarkable performance across various tasks. Notwithstanding, contemporary research primarily centers on enhancing the size and quality of…
Code CompletionSentenceSentence EmbeddingSentence-EmbeddingStable Code Technical Report
We introduce Stable Code, the first in our new-generation of code language models series, which serves as a general-purpose base code language model targeting code completion, reasoning, math, and other software engineer…
Code CompletionLanguage ModellingMathQuestion AnsweringPCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models
Prompt compression is an innovative method for efficiently condensing input prompts while preserving essential information. To facilitate quick-start services, user-friendly interfaces, and compatibility with common data…
Code CompletionFew-Shot LearningMathematical Problem-SolvingMultiple-choice+1Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case Study
Language model-based code completion models have quickly grown in use, helping thousands of developers write code in many different programming languages. However, research on code completion models typically focuses on …
Code CompletionHumanEvalLanguage ModellingRepoformer: Selective Retrieval for Repository-Level Code Completion
Recent advances in retrieval-augmented generation (RAG) have initiated a new era in repository-level code completion. However, the invariable use of retrieval in existing methods exposes issues in both efficiency and rob…
Code CompletionRAGRetrievalRetrieval-augmented Generation+1Token Alignment via Character Matching for Subword Completion
Generative models, widely utilized in various applications, can often struggle with prompts corresponding to partial tokens. This struggle stems from tokenization, where partial tokens fall out of distribution during inf…
Code CompletionCodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion
The rapid advancement of Large Language Models (LLMs) has brought about remarkable generative capabilities but also raised concerns about their potential misuse. While strategies like supervised fine-tuning and reinforce…
Code CompletionSafety AlignmentRepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion
Code Large Language Models (CodeLLMs) have demonstrated impressive proficiency in code completion tasks. However, they often fall short of fully understanding the extensive context of a project repository, such as the in…
Code CompletionLink PredictionRetrieval