https://github.com/huangd1999/soap
공식 코드EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
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/huawei-noah/noah-research
공식 코드Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis
https://github.com/humanity-s-last-code-exam/hlce
공식 코드Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?
https://github.com/hyu-nlp/revisiting-modularity
공식 코드Revisiting the Impact of Pursuing Modularity for Code Generation
https://github.com/iaar-shanghai/maintaincoder
공식 코드MaintainCoder: Maintainable Code Generation Under Dynamic Requirements
https://github.com/ianwalls/persona-code
공식 코드Personality-Guided Code Generation Using Large Language Models
https://github.com/ibm-granite/granite-code-models
공식 코드Granite Code Models: A Family of Open Foundation Models for Code Intelligence
https://github.com/ibm/limitations-lm-algorithmic-compositional-learning
공식 코드Limits of Transformer Language Models on Learning to Compose Algorithms
https://github.com/icetlab/codeprompteval
공식 코드The Impact of Prompt Programming on Function-Level Code Generation
https://github.com/ieit-yuan/yuan-2.0
공식 코드YUAN 2.0: A Large Language Model with Localized Filtering-based Attention
https://github.com/iljasir/copilotsolverforleetcode
공식 코드https://github.com/imamnurby/transducer-tuning
공식 코드Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs
https://github.com/imbernoulli/surge
공식 코드SURGE: On the Potential of Large Language Models as General-Purpose Surrogate Code Executors
https://github.com/imoneoi/openchat
공식 코드OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
https://github.com/infi-coder/infibench-evaluation-harness
공식 코드InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models
https://github.com/infi-coder/infibench-evaluator
공식 코드InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models
https://github.com/ink7-sudo/dependeval
공식 코드DependEval: Benchmarking LLMs for Repository Dependency Understanding
https://github.com/innovatingai/automind
공식 코드AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
https://github.com/instance-wise-ordered-transformer/IOT
공식 코드IOT: Instance-wise Layer Reordering for Transformer Structures
https://github.com/intelligent-cat-lab/codemind
공식 코드CodeMind: Evaluating Large Language Models for Code Reasoning
https://github.com/internlm/alchemistcoder
공식 코드AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data
https://github.com/internlm/swe-fixer
공식 코드SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution
https://github.com/ise-uet-vnu/openia
공식 코드Correctness Assessment of Code Generated by Large Language Models Using Internal Representations
https://github.com/ise-uet-vnu/rambo
공식 코드RAMBO: Enhancing RAG-based Repository-Level Method Body Completion
https://github.com/ise-uiuc/Repilot
공식 코드https://github.com/ise-uiuc/magicoder
공식 코드https://github.com/ise-uiuc/whitefox
공식 코드WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
https://github.com/ist-daslab/qigen
공식 코드QIGen: Generating Efficient Kernels for Quantized Inference on Large Language Models
https://github.com/iwangjian/Coding-Tutor
공식 코드https://github.com/j1mk1m/autoexperiment
공식 코드From Reproduction to Replication: Evaluating Research Agents with Progressive Code Masking
https://github.com/jaabmar/cp_fuse
공식 코드Copyright-Protected Language Generation via Adaptive Model Fusion
https://github.com/jabhinav/prompt-tuning-strikes-back-with-lopa
공식 코드Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation
https://github.com/java-bench/javabench
공식 코드JavaBench: A Benchmark of Object-Oriented Code Generation for Evaluating Large Language Models
https://github.com/jc-78/music2p
공식 코드Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design
https://github.com/jdeschena/sdtt
공식 코드Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
https://github.com/jeonghun3572/CoCoS
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.