Papers Code Search
“Code Search” 태그가 달린 논문 147편 · 필터 해제
Global Contrastive Batch Sampling via Optimization on Sample Permutations
Contrastive Learning has recently achieved state-of-the-art performance in a wide range of tasks. Many contrastive learning approaches use mined hard negatives to make batches more informative during training but these a…
Code SearchContrastive LearningSentenceSentence Embedding+1Exploring Representation-Level Augmentation for Code Search
Code search, which aims at retrieving the most relevant code fragment for a given natural language query, is a common activity in software development practice. Recently, contrastive learning is widely used in code searc…
Code SearchContrastive LearningData AugmentationContraCLM: Contrastive Learning For Causal Language Model
Despite exciting progress in causal language models, the expressiveness of the representations is largely limited due to poor discrimination ability. To remedy this issue, we present ContraCLM, a novel contrastive learni…
Code GenerationCode SearchContrastive LearningHumanEval+5CodeDSI: Differentiable Code Search
Reimplementing solutions to previously solved software engineering problems is not only inefficient but also introduces inadequate and error-prone code. Many existing methods achieve impressive performance on this issue …
Code GenerationCode SearchNatural Language QueriesText GenerationCSSAM:Code Search via Attention Matching of Code Semantics and Structures
Despite the continuous efforts in improving both the effectiveness and efficiency of code search, two issues remained unsolved. First, programming languages have inherent strong structural linkages, and feature mining of…
Code SearchDescriptiveXLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence
Recent advances in machine learning have significantly improved the understanding of source code data and achieved good performance on a number of downstream tasks. Open source repositories like GitHub enable this proces…
Code SearchNS3: Neuro-Symbolic Semantic Code Search
Semantic code search is the task of retrieving a code snippet given a textual description of its functionality. Recent work has been focused on using similarity metrics between neural embeddings of text and code. However…
Code SearchQuestion AnsweringRetrievalSentenceCoCoSoDa: Effective Contrastive Learning for Code Search
Code search aims to retrieve semantically relevant code snippets for a given natural language query. Recently, many approaches employing contrastive learning have shown promising results on code representation learning a…
Code SearchContrastive LearningData AugmentationRepresentation LearningOn the Transferability of Pre-trained Language Models for Low-Resource Programming Languages
A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a cor…
Code SearchCode SummarizationAccelerating Code Search with Deep Hashing and Code Classification
Code search is to search reusable code snippets from source code corpus based on natural languages queries. Deep learning-based methods of code search have shown promising results. However, previous methods focus on retr…
ClassificationCode ClassificationCode SearchDeep Hashing+1UniXcoder: Unified Cross-Modal Pre-training for Code Representation
Pre-trained models for programming languages have recently demonstrated great success on code intelligence. To support both code-related understanding and generation tasks, recent works attempt to pre-train unified encod…
Code CompletionCode SearchContrastive LearningDecoderCode Search based on Context-aware Code Translation
Code search is a widely used technique by developers during software development. It provides semantically similar implementations from a large code corpus to developers based on their queries. Existing techniques levera…
Code SearchCode TranslationTranslationWhat Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code
Recently, many pre-trained language models for source code have been proposed to model the context of code and serve as a basis for downstream code intelligence tasks such as code completion, code search, and code summar…
Code CompletionCode SearchCode SummarizationOn the Importance of Building High-quality Training Datasets for Neural Code Search
The performance of neural code search is significantly influenced by the quality of the training data from which the neural models are derived. A large corpus of high-quality query and code pairs is demanded to establish…
Code SearchRetrievalLearning Deep Semantic Model for Code Search using CodeSearchNet Corpus
Semantic code search is the task of retrieving relevant code snippet given a natural language query. Different from typical information retrieval tasks, code search requires to bridge the semantic gap between the program…
Code SearchInformation RetrievalRepresentation LearningRetrieval+2CodeRetriever: Unimodal and Bimodal Contrastive Learning for Code Search
In this paper, we propose the CodeRetriever model, which learns the function-level code semantic representations through large-scale code-text contrastive pre-training. We adopt two contrastive learning schemes in CodeRe…
Code SearchContrastive LearningText and Code Embeddings by Contrastive Pre-Training
Text embeddings are useful features in many applications such as semantic search and computing text similarity. Previous work typically trains models customized for different use cases, varying in dataset choice, trainin…
Code SearchLinear-Probe ClassificationNatural QuestionsPassage Ranking+3Generating Clarifying Questions for Query Refinement in Source Code Search
In source code search, a common information-seeking strategy involves providing a short initial query with a broad meaning, and then iteratively refining the query using terms gleaned from the results of subsequent searc…
Code SearchAstBERT: Enabling Language Model for Financial Code Understanding with Abstract Syntax Trees
Using the pre-trained language models to understand source codes has attracted increasing attention from financial institutions owing to the great potential to uncover financial risks. However, there are several challeng…
Clone DetectionCode SearchLanguage ModelingLanguage Modelling+1Analyzing CodeBERT's Performance on Natural Language Code Search
Large language models such as CodeBERT perform very well on tasks such as natural language code search. We show that this is most likely due to the high token overlap and similarity between the queries and the code in da…
Code Search