Llama-8B Teaches Itself Baby Steps to Deep Research Using RL
I've been tinkering with getting Llama-8B to bootstrap its own research skills through self-play. The model generates questions about documents, searches for answers, and then learns from its own successes/failures through RL (hacked up Unsloth's GRPO code). Started with just 23% accuracy on Apollo 13 mission report questions and hit 53% after less than an hour of training. Everything runs locally using open-source models. It's cool to see the model go from completely botching search queries to iteratively researching to get the right answer.
Llama-8B Teaches Itself Baby Steps to Deep Research Using RL launched on March 10, 2025 with 39 votes, #596 of 7,215 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Llama-8B Teaches Itself Baby Steps to Deep Research Using RL is a system that trains a small language model to improve its research abilities through reinforcement learning. The model generates questions about documents, searches for answers, and learns from its own results. Built with open-source tools and running locally, it demonstrated accuracy improvements from 23% to 53% on document-based questions in under an hour of training. It's designed for developers interested in self-improving language models and local AI experimentation.
written from the facts on this page · September 2026
From the sources
Autonomously train research-agent LLMs on custom data using reinforcement learning and self-verification. - dCaples/AutoDidact
Research exploring how small LLMs can autonomously enhance their own research and reasoning capabilities by generating, researching, and answering self-created question-answer pairs, learning agentic search via reinforcement learning. All running on a single RTX 4090! Credits: This project was built using Unsloth's Efficient GRPO code , and adds support for function calling and agentic loops. After just 100 steps of GRPO training (1 hour on a single RTX 4090 GPU), Llama-8B significantly improved its ability to research and answer questions from the Apollo 13 mission report. On a validation set of 68 questions, accuracy more than doubled from 23% to 59% . Through training, however, the model…from github.com
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