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Code Generation

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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/weixiangyan/codescope

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CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation

https://github.com/weixiangyan/codetransocean

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CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation

https://github.com/whuhsy/geo-fub

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Geo-FuB: A Method for Constructing an Operator-Function Knowledge Base for Geospatial Code Generation Tasks Using Large Language Models

https://github.com/willard-yuan/hashing-baseline-for-image-retrieval

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Deep Hashing with Category Mask for Fast Video Retrieval

https://github.com/wilyub/verithoughts

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VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification

https://github.com/wlchen0206/llm-sp

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Do LLM Evaluators Prefer Themselves for a Reason?

https://github.com/wshi83/ehragent

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EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records

https://github.com/wssun/trancs

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Code Search based on Context-aware Code Translation

https://github.com/wuhy68/parameter-efficient-moe

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Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks

https://github.com/wutong8023/versicode

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VersiCode: Towards Version-controllable Code Generation

https://github.com/wuxingyu-ai/llm4ec

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Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap

https://github.com/wuzhenyubuaa/sodgan

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Synthetic Data Supervised Salient Object Detection

https://github.com/wxy3596/asma-tune

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ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning

https://github.com/wyt2000/InverseCoder

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InverseCoder: Self-improving Instruction-Tuned Code LLMs with Inverse-Instruct

https://github.com/xingyaoww/code4struct

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Code4Struct: Code Generation for Few-Shot Event Structure Prediction

https://github.com/xingyaoww/leti

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LeTI: Learning to Generate from Textual Interactions

https://github.com/xiwenchao/omac-demo

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OMAC: A Broad Optimization Framework for LLM-Based Multi-Agent Collaboration

https://github.com/xlang-ai/arks

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EVOR: Evolving Retrieval for Code Generation

https://github.com/xlang-ai/spider2-v

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Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?

https://github.com/xpq-tech/code-llmedit

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Model Editing for LLMs4Code: How Far are We?

https://github.com/xsc1234/info-rag

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Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation

https://github.com/xuefeng-cs/erp

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Entropy-Reinforced Planning with Large Language Models for Drug Discovery

https://github.com/xyin-anl/Nodeology

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PEAR: A Robust and Flexible Automation Framework for Ptychography Enabled by Multiple Large Language Model Agents

https://github.com/yale-nlp/code-llm-contamination

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Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models

https://github.com/yangling0818/buffer-of-thought-llm

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Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

https://github.com/yaof20/real

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Training Language Models to Generate Quality Code with Program Analysis Feedback

https://github.com/yaxirhuxxain/Source-Code-Suggestion

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CodeGRU: Context-aware Deep Learning with Gated Recurrent Unit for Source Code Modeling

https://github.com/yerbapage/detectcodegpt

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Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers

https://github.com/yihaop/dreamstruct

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DreamStruct: Understanding Slides and User Interfaces via Synthetic Data Generation

https://github.com/yili-hong/StatLLM

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Performance Evaluation of Large Language Models in Statistical Programming

https://github.com/yilinjz/astchunk

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cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax Tree

https://github.com/yiqingxyq/RepoST

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RepoST: Scalable Repository-Level Coding Environment Construction with Sandbox Testing

https://github.com/yiqingxyq/codebenchgen

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CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks

https://github.com/yongchao98/codesteer-v1.0

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CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance

https://github.com/yongchao98/r1-code-interpreter

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R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning

https://github.com/yongkdu/faircode

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FairCoder: Evaluating Social Bias of LLMs in Code Generation

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