SOTAVerified

Code Search

The goal of Code Search is to retrieve code fragments from a large code corpus that most closely match a developer’s intent, which is expressed in natural language.

Source: When Deep Learning Met Code Search

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 125 papers

TitleStatusHype
CodeT5+: Open Code Large Language Models for Code Understanding and GenerationCode0
The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and GenerationCode1
Code Execution with Pre-trained Language ModelsCode0
REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search ModelsCode0
Neuro-symbolic Zero-Shot Code Cloning with Cross-Language Intermediate Representation—0
One Adapter for All Programming Languages? Adapter Tuning for Code Search and SummarizationCode1
Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities—0
You Don't Know Search: Helping Users Find Code by Automatically Evaluating Alternative Queries—0
Global Contrastive Batch Sampling via Optimization on Sample PermutationsCode0
Exploring Representation-Level Augmentation for Code SearchCode1
ContraCLM: Contrastive Learning For Causal Language ModelCode1
CodeDSI: Differentiable Code Search—0
CSSAM:Code Search via Attention Matching of Code Semantics and Structures—0
XLCoST: A Benchmark Dataset for Cross-lingual Code IntelligenceCode1
NS3: Neuro-Symbolic Semantic Code SearchCode0
CoCoSoDa: Effective Contrastive Learning for Code Search—0
On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages—0
Accelerating Code Search with Deep Hashing and Code Classification—0
UniXcoder: Unified Cross-Modal Pre-training for Code RepresentationCode1
Code Search based on Context-aware Code TranslationCode1
On the Importance of Building High-quality Training Datasets for Neural Code SearchCode1
What Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source CodeCode0
Learning Deep Semantic Model for Code Search using CodeSearchNet CorpusCode1
CodeRetriever: Unimodal and Bimodal Contrastive Learning for Code SearchCode0
Generating Clarifying Questions for Query Refinement in Source Code SearchCode0
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All datasetsCodeSearchNetCoDescCodeXGLUE - AdvTestCodeSearchNet - RubyCodeXGLUE - WebQueryTestCoIR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1cpt-code MOverall93.5—Unverified
2cpt-code SOverall93.4—Unverified
3CodeT5+ 770MOverall77.4—Unverified
4GraphCodeBERTOverall77.4—Unverified
5CodeT5+ 220MOverall77.1—Unverified
6CodeBERTOverall76—Unverified
#ModelMetricClaimedVerifiedStatus
1Self-attentionTest MRR0.84—Unverified
2NBOWTest MRR0.81—Unverified
3RNNTest MRR0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeT5+ 770MMRR44.7—Unverified
2CodeT5+ 220MMRR43.3—Unverified
3CodeBERTMRR27.19—Unverified
#ModelMetricClaimedVerifiedStatus
1Uni-SBTMRR0.36—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeBERTAccuracy47.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Voyage-code-002nDCG@1056.26—Unverified