Papers Code Completion
“Code Completion” 태그가 달린 논문 280편 · 필터 해제
EduBot -- Can LLMs Solve Personalized Learning and Programming Assignments?
The prevalence of Large Language Models (LLMs) is revolutionizing the process of writing code. General and code LLMs have shown impressive performance in generating standalone functions and code-completion tasks with one…
Code CompletionCode GenerationRTLRepoCoder: Repository-Level RTL Code Completion through the Combination of Fine-Tuning and Retrieval Augmentation
As an essential part of modern hardware design, manually writing Register Transfer Level (RTL) code such as Verilog is often labor-intensive. Following the tremendous success of large language models (LLMs), researchers …
Code CompletionRAGRetrieval-augmented GenerationCCCI: Code Completion with Contextual Information for Complex Data Transfer Tasks Using Large Language Models
Unlike code generation, which involves creating code from scratch, code completion focuses on integrating new lines or blocks of code into an existing codebase. This process requires a deep understanding of the surroundi…
Code CompletionCode GenerationObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Language models (LMs) have become a staple of the code-writing toolbox. Their pre-training recipe has, however, remained stagnant over recent years, barring the occasional changes in data sourcing and filtering strategie…
Code CompletionCode GenerationLibrary-Oriented Code GenerationLogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation
We introduce LogQuant, a groundbreaking 2-bit quantization technique for KV Cache in large language model (LLM) inference, delivering substantial memory savings while preserving superior performance. Previous methods eit…
Code CompletionLanguage ModelingLanguage ModellingLarge Language Model+2On Explaining (Large) Language Models For Code Using Global Code-Based Explanations
In recent years, Language Models for Code (LLM4Code) have significantly changed the landscape of software engineering (SE) on downstream tasks, such as code generation, by making software development more efficient. Ther…
Code CompletionCode GenerationCASTLE: Benchmarking Dataset for Static Code Analyzers and LLMs towards CWE Detection
Identifying vulnerabilities in source code is crucial, especially in critical software components. Existing methods such as static analysis, dynamic analysis, formal verification, and recently Large Language Models are w…
BenchmarkingCode ClassificationCode CompletionVulnerability DetectionEnhancing High-Quality Code Generation in Large Language Models with Comparative Prefix-Tuning
Large Language Models (LLMs) have been widely adopted in commercial code completion engines, significantly enhancing coding efficiency and productivity. However, LLMs may generate code with quality issues that violate co…
Code CompletionCode GenerationFEA-Bench: A Benchmark for Evaluating Repository-Level Code Generation for Feature Implementation
Implementing new features in repository-level codebases is a crucial application of code generation models. However, current benchmarks lack a dedicated evaluation framework for this capability. To fill this gap, we intr…
Code CompletionCode GenerationGenAI for Simulation Model in Model-Based Systems Engineering
Generative AI (GenAI) has demonstrated remarkable capabilities in code generation, and its integration into complex product modeling and simulation code generation can significantly enhance the efficiency of the system d…
Code CompletionCode GenerationmodelSolBench: A Dataset and Benchmark for Evaluating Functional Correctness in Solidity Code Completion and Repair
Smart contracts are crucial programs on blockchains, and their immutability post-deployment makes functional correctness vital. Despite progress in code completion models, benchmarks for Solidity, the primary smart contr…
Code CompletionCode RepairRetrievalAlchemist: Towards the Design of Efficient Online Continual Learning System
Continual learning has become a promising solution to refine large language models incrementally by leveraging user feedback. In particular, online continual learning - iteratively training the model with small batches o…
Code CompletionContinual LearningAutomated Code Generation and Validation for Software Components of Microcontrollers
This paper proposes a method for generating software components for embedded systems, integrating seamlessly into existing implementations without developer intervention. We demonstrate this by automatically generating h…
Code CompletionCode GenerationRAGRetrieval+1LongSpec: Long-Context Speculative Decoding with Efficient Drafting and Verification
Speculative decoding has become a promising technique to mitigate the high inference latency of autoregressive decoding in Large Language Models (LLMs). Despite its promise, the effective application of speculative decod…
Code CompletionComparative Analysis of Large Language Models for Context-Aware Code Completion using SAFIM Framework
The advent of Large Language Models (LLMs) has revolutionized code completion, transforming it into a more intelligent and context-aware feature in modern integrated development environments. These advancements have sign…
Code CompletionCode GenerationHow to Get Your LLM to Generate Challenging Problems for Evaluation
The pace of evolution of Large Language Models (LLMs) necessitates new approaches for rigorous and comprehensive evaluation. Traditional human annotation is increasingly impracticable due to the complexities and costs in…
Code CompletionMathQuestion AnsweringMechanistic Understanding of Language Models in Syntactic Code Completion
Recently, language models (LMs) have shown impressive proficiency in code generation tasks, especially when fine-tuned on code-specific datasets, commonly known as Code LMs. However, our understanding of the internal dec…
Code CompletionCode GenerationMathFimer: Enhancing Mathematical Reasoning by Expanding Reasoning Steps through Fill-in-the-Middle Task
Mathematical reasoning represents a critical frontier in advancing large language models (LLMs). While step-by-step approaches have emerged as the dominant paradigm for mathematical problem-solving in LLMs, the quality o…
Code CompletionGSM8KMathMathematical Problem-Solving+1GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation
Large Language Models (LLMs) are becoming integral to daily life, showcasing their vast potential across various Natural Language Processing (NLP) tasks. Beyond NLP, LLMs are increasingly used in software development tas…
Bug fixingCode CompletionCode GenerationCode Translation+1Improving FIM Code Completions via Context & Curriculum Based Learning
Fill-in-the-Middle (FIM) models play a vital role in code completion tasks, leveraging both prefix and suffix context to provide more accurate and contextually relevant suggestions. This paper presents approaches to impr…
Code Completion