DataFoundry: Evolving Data Preparators via Recursive Self-Improvement
cs.CL
Submitted: 2026-08-30
Updated: 2026-08-30
Terminology
Sources
- Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
- DeepPrep: An LLM-Powered Agentic System for Autonomous Data Preparation
- Autodata: An agentic data scientist to create high quality synthetic data
- Recursive Harness Self-Improvement
- Meta-Harness: End-to-End Optimization of Model Harnesses
- Infinity Instruct: Scaling Instruction Selection and Synthesis to Enhance Language Models
- DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
- DataPrep-Bench: Benchmarking LLMs as Training Data Preparators
- SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
- Skill-R1: Agent Skill Evolution via Reinforcement Learning
- Self-Instruct: Aligning Language Models with Self-Generated Instructions
- WizardLM: Empowering large pre-trained language models to follow complex instructions
- Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward
- AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
- CoT-Self-Instruct: Building high-quality synthetic prompts for reasoning and non-reasoning tasks
- CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
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