kRAIG: A Natural Language-Driven Agent for Automated DataOps Pipeline Generation
Fuente:
arXiv
Saved in:
| Main Authors: | Siva, Rohan, Cheung, Kai, Li, Lichi, Sundaram, Ganesh |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
AutoIOT: LLM-Driven Automated Natural Language Programming for AIoT Applications
by: Shen, Leming, et al.
Published: (2025)
by: Shen, Leming, et al.
Published: (2025)
DataOps-driven CI/CD for analytics repositories
by: Valiaiev, Dmytro
Published: (2025)
by: Valiaiev, Dmytro
Published: (2025)
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
by: Liao, Yuan, et al.
Published: (2024)
by: Liao, Yuan, et al.
Published: (2024)
Deployability-Centric Infrastructure-as-Code Generation: Fail, Learn, Refine, and Succeed through LLM-Empowered DevOps Simulation
by: Zhang, Tianyi, et al.
Published: (2025)
by: Zhang, Tianyi, et al.
Published: (2025)
APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets
by: Liu, Zuxin, et al.
Published: (2024)
by: Liu, Zuxin, et al.
Published: (2024)
Terminal Agents Suffice for Enterprise Automation
by: Bechard, Patrice, et al.
Published: (2026)
by: Bechard, Patrice, et al.
Published: (2026)
Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models
by: Liu, Ruibang, et al.
Published: (2024)
by: Liu, Ruibang, et al.
Published: (2024)
Evaluating Retrieval-Augmented Generation Variants for Natural Language-Based SQL and API Call Generation
by: Marketsmüller, Michael, et al.
Published: (2026)
by: Marketsmüller, Michael, et al.
Published: (2026)
Co-Learning: Code Learning for Multi-Agent Reinforcement Collaborative Framework with Conversational Natural Language Interfaces
by: Yu, Jiapeng, et al.
Published: (2024)
by: Yu, Jiapeng, et al.
Published: (2024)
DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle
by: Tang, Yuheng, et al.
Published: (2026)
by: Tang, Yuheng, et al.
Published: (2026)
CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
by: Islam, Md. Ashraful, et al.
Published: (2025)
by: Islam, Md. Ashraful, et al.
Published: (2025)
IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models
by: Imtiaz, Sayem Mohammad, et al.
Published: (2025)
by: Imtiaz, Sayem Mohammad, et al.
Published: (2025)
A Code Comprehension Benchmark for Large Language Models for Code
by: Havare, Jayant, et al.
Published: (2025)
by: Havare, Jayant, et al.
Published: (2025)
Dafny as Verification-Aware Intermediate Language for Code Generation
by: Li, Yue Chen, et al.
Published: (2025)
by: Li, Yue Chen, et al.
Published: (2025)
Semantically Aligned Question and Code Generation for Automated Insight Generation
by: Singha, Ananya, et al.
Published: (2024)
by: Singha, Ananya, et al.
Published: (2024)
DocAgent: A Multi-Agent System for Automated Code Documentation Generation
by: Yang, Dayu, et al.
Published: (2025)
by: Yang, Dayu, et al.
Published: (2025)
BenchGuard: Who Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks
by: Tu, Xinming, et al.
Published: (2026)
by: Tu, Xinming, et al.
Published: (2026)
Exploring Data-Efficient Adaptation of Large Language Models for Code Generation
by: Jiang, Xue, et al.
Published: (2024)
by: Jiang, Xue, et al.
Published: (2024)
MOSS: Enabling Code-Driven Evolution and Context Management for AI Agents
by: Zhu, Ming, et al.
Published: (2024)
by: Zhu, Ming, et al.
Published: (2024)
Can Large Language Models Transform Natural Language Intent into Formal Method Postconditions?
by: Endres, Madeline, et al.
Published: (2023)
by: Endres, Madeline, et al.
Published: (2023)
SEW: Self-Evolving Agentic Workflows for Automated Code Generation
by: Liu, Siwei, et al.
Published: (2025)
by: Liu, Siwei, et al.
Published: (2025)
Generating Verifiable Chain of Thoughts from Exection-Traces
by: Thakur, Shailja, et al.
Published: (2025)
by: Thakur, Shailja, et al.
Published: (2025)
Effective LLM-Driven Code Generation with Pythoness
by: Levin, Kyla H., et al.
Published: (2025)
by: Levin, Kyla H., et al.
Published: (2025)
VisCoder2: Building Multi-Language Visualization Coding Agents
by: Ni, Yuansheng, et al.
Published: (2025)
by: Ni, Yuansheng, et al.
Published: (2025)
Evaluating LLMs on Sequential API Call Through Automated Test Generation
by: Huang, Yuheng, et al.
Published: (2025)
by: Huang, Yuheng, et al.
Published: (2025)
Is Open Source the Future of AI? A Data-Driven Approach
by: Vake, Domen, et al.
Published: (2025)
by: Vake, Domen, et al.
Published: (2025)
CodeS: Natural Language to Code Repository via Multi-Layer Sketch
by: Zan, Daoguang, et al.
Published: (2024)
by: Zan, Daoguang, et al.
Published: (2024)
Natural Language-Oriented Programming (NLOP): Towards Democratizing Software Creation
by: Beheshti, Amin
Published: (2024)
by: Beheshti, Amin
Published: (2024)
Text2BIM: Generating Building Models Using a Large Language Model-based Multi-Agent Framework
by: Du, Changyu, et al.
Published: (2024)
by: Du, Changyu, et al.
Published: (2024)
CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
by: Yan, Weixiang, et al.
Published: (2023)
by: Yan, Weixiang, et al.
Published: (2023)
SWE-smith: Scaling Data for Software Engineering Agents
by: Yang, John, et al.
Published: (2025)
by: Yang, John, et al.
Published: (2025)
Code Broker: A Multi-Agent System for Automated Code Quality Assessment
by: Attrah, Samer
Published: (2026)
by: Attrah, Samer
Published: (2026)
SWE-AGI: Benchmarking Specification-Driven Software Construction with MoonBit in the Era of Autonomous Agents
by: Zhang, Zhirui, et al.
Published: (2026)
by: Zhang, Zhirui, et al.
Published: (2026)
Towards Automated Smart Contract Generation: Evaluation, Benchmarking, and Retrieval-Augmented Repair
by: Chen, Zaoyu, et al.
Published: (2025)
by: Chen, Zaoyu, et al.
Published: (2025)
The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation
by: Gao, Shuzheng, et al.
Published: (2025)
by: Gao, Shuzheng, et al.
Published: (2025)
Semantic Caching and Intent-Driven Context Optimization for Multi-Agent Natural Language to Code Systems
by: Singh, Harmohit
Published: (2026)
by: Singh, Harmohit
Published: (2026)
DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code
by: Sharma, Pratyush Nidhi, et al.
Published: (2025)
by: Sharma, Pratyush Nidhi, et al.
Published: (2025)
Improving Code Generation by Training with Natural Language Feedback
by: Chen, Angelica, et al.
Published: (2023)
by: Chen, Angelica, et al.
Published: (2023)
Planning to Explore: Curiosity-Driven Planning for LLM Test Generation
by: Amayuelas, Alfonso, et al.
Published: (2026)
by: Amayuelas, Alfonso, et al.
Published: (2026)
ACCeLLiuM: Supervised Fine-Tuning for Automated OpenACC Pragma Generation
by: Jhaveri, Samyak, et al.
Published: (2025)
by: Jhaveri, Samyak, et al.
Published: (2025)
Similar Items
-
AutoIOT: LLM-Driven Automated Natural Language Programming for AIoT Applications
by: Shen, Leming, et al.
Published: (2025) -
DataOps-driven CI/CD for analytics repositories
by: Valiaiev, Dmytro
Published: (2025) -
Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learned
by: Liao, Yuan, et al.
Published: (2024) -
Deployability-Centric Infrastructure-as-Code Generation: Fail, Learn, Refine, and Succeed through LLM-Empowered DevOps Simulation
by: Zhang, Tianyi, et al.
Published: (2025) -
APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets
by: Liu, Zuxin, et al.
Published: (2024)