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Code Completion

Papers

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Showing 101–150 of 212 papers

TitleStatusHype
Time-Efficient Code Completion Model for the R Programming LanguageCode0
Automating Code-Related Tasks Through Transformers: The Impact of Pre-trainingCode0
Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case StudyCode0
MERGE: Fast Private Text GenerationCode0
Code Completion with Neural Attention and Pointer NetworksCode0
Large Language Models of Code Fail at Completing Code with Potential BugsCode0
CodeT5+: Open Code Large Language Models for Code Understanding and GenerationCode0
Eclipse CDT code analysis and unit testingCode0
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion—0
Black-Box Adversarial Attacks on LLM-Based Code Completion—0
SolBench: A Dataset and Benchmark for Evaluating Functional Correctness in Solidity Code Completion and Repair—0
AKD : Adversarial Knowledge Distillation For Large Language Models Alignment on Coding tasks—0
Alchemist: Towards the Design of Efficient Online Continual Learning System—0
Alignment-Augmented Speculative Decoding with Alignment Sampling and Conditional Verification—0
All You Need Is Logs: Improving Code Completion by Learning from Anonymous IDE Usage Logs—0
Insights from the Usage of the Ansible Lightspeed Code Completion Service—0
A Review of Repository Level Prompting for LLMs—0
A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning—0
A Static Evaluation of Code Completion by Large Language Models—0
Attention Alignment and Flexible Positional Embeddings Improve Transformer Length Extrapolation—0
Augur: a Modeling Language for Data-Parallel Probabilistic Inference—0
Automated Code Generation and Validation for Software Components of Microcontrollers—0
Benchmarking Causal Study to Interpret Large Language Models for Source Code—0
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion—0
Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents—0
Examining Zero-Shot Vulnerability Repair with Large Language Models—0
CCCI: Code Completion with Contextual Information for Complex Data Transfer Tasks Using Large Language Models—0
Chain of Agents: Large Language Models Collaborating on Long-Context Tasks—0
CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt—0
CodeCipher: Learning to Obfuscate Source Code Against LLMs—0
Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs—0
Code Completion using Neural Attention and Byte Pair Encoding—0
CodeGemma: Open Code Models Based on Gemma—0
CodeMixBench: Evaluating Large Language Models on Code Generation with Code-Mixed Prompts—0
Coeditor: Leveraging Contextual Changes for Multi-round Code Auto-editing—0
Comparative Analysis of Large Language Models for Context-Aware Code Completion using SAFIM Framework—0
Compilable Neural Code Generation with Compiler Feedback—0
Context Composing for Full Line Code Completion—0
ContextModule: Improving Code Completion via Repository-level Contextual Information—0
Critique Ability of Large Language Models—0
Curriculum Learning for Small Code Language Models—0
DeepVS: An Efficient and Generic Approach for Source Code Modeling Usage—0
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates—0
Dynamic Neural Program Embeddings for Program Repair—0
EduBot -- Can LLMs Solve Personalized Learning and Programming Assignments?—0
Enhancing LLM-Based Coding Tools through Native Integration of IDE-Derived Static Context—0
Evaluating Long Range Dependency Handling in Code Generation Models using Multi-Step Key Retrieval—0
ExecRepoBench: Multi-level Executable Code Completion Evaluation—0
Fast and Memory-Efficient Neural Code Completion—0
FastDraft: How to Train Your Draft—0
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All datasetsSAFIMCodeXGLUE - Github Java CorpusCodeXGLUE - PY150DotPromptsDefects4JRambo Benchmark

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1deepseek-coder-33b-baseAverage69.01—Unverified
2deepseek-coder-6.7b-baseAverage63.4—Unverified
3starcoderbaseAverage55.54—Unverified
4gpt-4-1106-previewAverage53.28—Unverified
5CodeLlama-13b-hfAverage52.78—Unverified
6deepseek-coder-1.3b-baseAverage52.63—Unverified
7CodeLlama-34b-hfAverage49.66—Unverified
8CodeLlama-7b-hfAverage45—Unverified
9gpt-3.5-turbo-0301Average40.86—Unverified
10incoder-6BAverage33.79—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeGPT-adaptedAccuracy (token-level)77.13—Unverified
2CodeT5+ 770MEM (line-level)37.9—Unverified
3CodeT5+ 220MEM (line-level)35.17—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeGPT-adaptedAccuracy (token-level)75.11—Unverified
2CodeT5+ 770MEM (line-level)44.86—Unverified
3CodeT5+ 220MEM (line-level)43.42—Unverified
#ModelMetricClaimedVerifiedStatus
1SantaCoder-MGDCompilation Rate73.03—Unverified
2SantaCoderCompilation Rate59.97—Unverified
3SantaCoderCompilation Rate59.79—Unverified
#ModelMetricClaimedVerifiedStatus
1RamboCompilation Rate76.47—Unverified
2RepoCoderCompilation Rate74.02—Unverified
#ModelMetricClaimedVerifiedStatus
1RamboCompilation Rate61.7—Unverified
2RepoCoderCompilation Rate58.09—Unverified