https://github.com/sparksofagi/mhpp
공식 코드MHPP: Exploring the Capabilities and Limitations of Language Models Beyond Basic Code Generation
Papers with Code 아카이브
Code Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 28
- 보존된 평가 기록
- 241
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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sraedler/MDE_for_ML_Generation
공식 코드Code Generation for Machine Learning using Model-Driven Engineering and SysML
https://github.com/stable-lab/MAGE-A-Multi-Agent-Engine-for-Automated-RTL-Code-Generation
공식 코드MAGE: A Multi-Agent Engine for Automated RTL Code Generation
https://github.com/stable-lab/pro-v
공식 코드PRO-V: An Efficient Program Generation Multi-Agent System for Automatic RTL Verification
https://github.com/stonybrooknlp/appworld
공식 코드AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
https://github.com/sunblaze-ucb/intuitor
공식 코드https://github.com/sunblaze-ucb/verina
공식 코드https://github.com/sunnynexus/search-o1
공식 코드https://github.com/swe-rebench/swe-bench-fork
공식 코드https://github.com/sweetpeach/ReCode
공식 코드https://github.com/swtheing/pf-ppo-rlhf
공식 코드Policy Filtration in RLHF to Fine-Tune LLM for Code Generation
https://github.com/symforce-org/symforce
공식 코드SymForce: Symbolic Computation and Code Generation for Robotics
https://github.com/sysuselab/rustevo
공식 코드RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation
https://github.com/t-muras/ai-code-analysis
공식 코드https://github.com/taoyds/typesql
공식 코드TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation
https://github.com/teakinboyewa/spatialanalysisagent
공식 코드GIS Copilot: Towards an Autonomous GIS Agent for Spatial Analysis
https://github.com/tech-srl/slm-code-generation
공식 코드https://github.com/telekom/indiceval-xl
공식 코드IndicEval-XL: Bridging Linguistic Diversity in Code Generation Across Indic Languages
https://github.com/terryyz/ice-score
공식 코드ICE-Score: Instructing Large Language Models to Evaluate Code
https://github.com/terryyz/llm-code-eval
공식 코드ICE-Score: Instructing Large Language Models to Evaluate Code
https://github.com/text2app/Text2App
공식 코드Text2App: A Framework for Creating Android Apps from Text Descriptions
https://github.com/tguttzeit/ai-code-examination
공식 코드https://github.com/theoxo/self-repair
공식 코드https://github.com/thomasjoshi/agents-never-forget
공식 코드https://github.com/thomaspzollo/prompt_risk
공식 코드Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
https://github.com/thu-bpm/chatgpt-sql
공식 코드A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability
https://github.com/thudm/datascibench
공식 코드https://github.com/thunlp/ChartCoder
공식 코드ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation
https://github.com/thunlp/debugbench
공식 코드DebugBench: Evaluating Debugging Capability of Large Language Models
https://github.com/thunlp/matplotagent
공식 코드MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization
https://github.com/thunlp/tritonbench
공식 코드TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators
https://github.com/tim120526/AutoM3L
공식 코드AutoM3L: An Automated Multimodal Machine Learning Framework with Large Language Models
https://github.com/tonybeltramelli/pix2code
공식 코드pix2code: Generating Code from a Graphical User Interface Screenshot
https://github.com/trishullab/clever
공식 코드CLEVER: A Curated Benchmark for Formally Verified Code Generation
https://github.com/trishullab/clever-prover
공식 코드CLEVER: A Curated Benchmark for Formally Verified Code Generation
https://github.com/trust4ai/astral
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.