SOTAVerified

Code Completion

Papers

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Showing 76–100 of 212 papers

TitleStatusHype
Context Composing for Full Line Code Completion—0
Compilable Neural Code Generation with Compiler Feedback—0
A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning—0
AKD : Adversarial Knowledge Distillation For Large Language Models Alignment on Coding tasks—0
SolBench: A Dataset and Benchmark for Evaluating Functional Correctness in Solidity Code Completion and Repair—0
Comparative Analysis of Large Language Models for Context-Aware Code Completion using SAFIM Framework—0
Coeditor: Leveraging Contextual Changes for Multi-round Code Auto-editing—0
Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents—0
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion—0
A Review of Repository Level Prompting for LLMs—0
CodeMixBench: Evaluating Large Language Models on Code Generation with Code-Mixed Prompts—0
Jailbreak Attacks and Defenses Against Large Language Models: A Survey—0
Benchmarking Causal Study to Interpret Large Language Models for Source Code—0
HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding—0
Insights from the Usage of the Ansible Lightspeed Code Completion Service—0
JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking—0
KV Prediction for Improved Time to First Token—0
Automated Code Generation and Validation for Software Components of Microcontrollers—0
TaskEval: Assessing Difficulty of Code Generation Tasks for Large Language Models—0
GraphCodeBERT: Pre-training Code Representations with Data Flow—0
CodeGemma: Open Code Models Based on Gemma—0
Horizon-Length Prediction: Advancing Fill-in-the-Middle Capabilities for Code Generation with Lookahead Planning—0
Interpretability Illusions in the Generalization of Simplified Models—0
Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions—0
All You Need Is Logs: Improving Code Completion by Learning from Anonymous IDE Usage Logs—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