FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents explores FT-Dojo automates LLM fine-tuning with agents to streamline domain-specific model optimization.. Commercial viability score: 8/10 in LLM Fine-Tuning.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisPostTrainBench: Can LLM Agents Automate LLM Post-Training?Viability: 7.0
- Builds On ThisToward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading TasksViability: 3.0
- Builds On ThisCan RL Improve Generalization of LLM Agents? An Empirical StudyViability: 2.0
- Builds On ThisRetrieval-Augmented LLM Agents: Learning to Learn from ExperienceViability: 7.0
- Builds On ThisFine-Tuning Large Language Models for Cooperative Tactical Deconfliction of Small Unmanned Aerial Systems