Papers Code Completion
“Code Completion” 태그가 달린 논문 280편 · 필터 해제
ExecRepoBench: Multi-level Executable Code Completion Evaluation
Code completion has become an essential tool for daily software development. Existing evaluation benchmarks often employ static methods that do not fully capture the dynamic nature of real-world coding environments and f…
Code CompletionContextModule: Improving Code Completion via Repository-level Contextual Information
Large Language Models (LLMs) have demonstrated impressive capabilities in code completion tasks, where they assist developers by predicting and generating new code in real-time. However, existing LLM-based code completio…
Code CompletionProtect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
Recent years have witnessed the emerging trend of extensions in modern Integrated Development Environments (IDEs) like Visual Studio Code (VSCode) that significantly enhance developer productivity. Especially, popular AI…
Code CompletionLibEvolutionEval: A Benchmark and Study for Version-Specific Code Generation
Recent advancements in code completion models have primarily focused on local file contexts. However, these studies do not fully capture the complexity of real-world software development, which often requires the use of …
Code CompletionCode GenerationFastDraft: How to Train Your Draft
Speculative Decoding has gained popularity as an effective technique for accelerating the auto-regressive inference process of Large Language Models. However, Speculative Decoding entirely relies on the availability of e…
BenchmarkingCode CompletionLarge Language ModelCoCoP: Enhancing Text Classification with LLM through Code Completion Prompt
Text classification is a fundamental task in natural language processing (NLP), and large language models (LLMs) have demonstrated their capability to perform this task across various domains. However, the performance of…
ClassificationCode CompletionFew-Shot Learningtext-classification+1GitChameleon: Unmasking the Version-Switching Capabilities of Code Generation Models
The rapid evolution of software libraries presents a significant challenge for code generation models, which must adapt to frequent version updates while maintaining compatibility with previous versions. Existing code co…
Code CompletionCode GenerationJudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking
Accurate document retrieval is crucial for the success of retrieval-augmented generation (RAG) applications, including open-domain question answering and code completion. While large language models (LLMs) have been empl…
Code CompletionOpen-Domain Question AnsweringQuestion AnsweringRAG+4Can Language Models Replace Programmers for Coding? REPOCOD Says 'Not Yet'
Recently, a number of repository-level code generation benchmarks-such as CoderEval, DevEval, RepoEval, RepoBench, and LongCodeArena-have emerged to evaluate the capabilities of large language models (LLMs) beyond standa…
Code CompletionCode GenerationHumanEvalmbpp+1M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation
Repository-level code completion has drawn great attention in software engineering, and several benchmark datasets have been introduced. However, existing repository-level code completion benchmarks usually focus on a li…
Code CompletionBuilding A Coding Assistant via the Retrieval-Augmented Language Model
Pretrained language models have shown strong effectiveness in code-related tasks, such as code retrieval, code generation, code summarization, and code completion tasks. In this paper, we propose COde assistaNt viA retri…
Code CompletionCode GenerationCode SummarizationLanguage Modeling+3Contextual Augmented Multi-Model Programming (CAMP): A Hybrid Local-Cloud Copilot Framework
The advancements in cloud-based Large Languages Models (LLMs) have revolutionized AI-assisted programming. However, their integration into certain local development environments like ones within the Apple software ecosys…
Code CompletionRAGRetrieval-augmented GenerationaiXcoder-7B: A Lightweight and Effective Large Language Model for Code Processing
Large Language Models (LLMs) have been widely used in code completion, and researchers are focusing on scaling up LLMs to improve their accuracy. However, larger LLMs have lower inference efficiency, affecting developers…
AttributeCode CompletionLanguage ModelingLanguage Modelling+1KV Prediction for Improved Time to First Token
Inference with transformer-based language models begins with a prompt processing step. In this step, the model generates the first output token and stores the KV cache needed for future generation steps. This prompt proc…
Code CompletionCPUHumanEvalPrediction+1CursorCore: Assist Programming through Aligning Anything
Large language models have been successfully applied to programming assistance tasks, such as code completion, code insertion, and instructional code editing. However, these applications remain insufficiently automated a…
Code CompletionCodeCipher: Learning to Obfuscate Source Code Against LLMs
While large code language models have made significant strides in AI-assisted coding tasks, there are growing concerns about privacy challenges. The user code is transparent to the cloud LLM service provider, inducing ri…
Code CompletionvalidHorizon-Length Prediction: Advancing Fill-in-the-Middle Capabilities for Code Generation with Lookahead Planning
Fill-in-the-Middle (FIM) has become integral to code language models, enabling generation of missing code given both left and right contexts. However, the current FIM training paradigm, which reorders original training s…
Code CompletionCode GenerationCodev-Bench: How Do LLMs Understand Developer-Centric Code Completion?
Code completion, a key downstream task in code generation, is one of the most frequent and impactful methods for enhancing developer productivity in software development. As intelligent completion tools evolve, we need a…
Code CompletionCode GenerationRAMBO: Enhancing RAG-based Repository-Level Method Body Completion
Code completion is essential in software development, helping developers by predicting code snippets based on context. Among completion tasks, Method Body Completion (MBC) is particularly challenging as it involves gener…
Code CompletionCode GenerationRAGStatically Contextualizing Large Language Models with Typed Holes
Large language models (LLMs) have reshaped the landscape of program synthesis. However, contemporary LLM-based code completion systems often hallucinate broken code because they lack appropriate context, particularly whe…
Code CompletionCode GenerationProgram Synthesis