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Code Generation
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Code Generation is an important field to predict explicit code or program structure from multimodal data sources such as incomplete code, programs in another programming language, natural language descriptions or execution examples. Code Generation tools can assist the development of automatic programming tools to improve programming productivity.
Source: Deep Learning for Source Code Modeling and Generation
Image source: Measuring Coding Challenge Competence With APPS
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SlideCoder: Layout-aware RAG-enhanced Hierarchical Slide Generation from Design
Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models
Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
LLMs Caught in the Crossfire: Malware Requests and Jailbreak Challenges
Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation
VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code
Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code
CP-Bench: Evaluating Large Language Models for Constraint Modelling
Can Theoretical Physics Research Benefit from Language Agents?
DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes
hdl2v: A Code Translation Dataset for Enhanced LLM Verilog Generation
Demonstrations of Integrity Attacks in Multi-Agent Systems
ICPC-Eval: Probing the Frontiers of LLM Reasoning with Competitive Programming Contests
ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
Deployability-Centric Infrastructure-as-Code Generation: An LLM-based Iterative Framework
Seed-Coder: Let the Code Model Curate Data for Itself
From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context
VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code Generation
CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking
Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems
Matter-of-Fact: A Benchmark for Verifying the Feasibility of Literature-Supported Claims in Materials Science
Rethinking the effects of data contamination in Code Intelligence
Adaptive Graph Pruning for Multi-Agent Communication
Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning
DiaBlo: Diagonal Blocks Are Sufficient For Finetuning
Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
SALAD: Systematic Assessment of Machine Unlearing on LLM-Aided Hardware Design
ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code
Legal Compliance Evaluation of Smart Contracts Generated By Large Language Models
CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval
A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming
SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation
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