MuninAI: A Self-Hosted Agentic Framework for Independent Research Groups

Key points

• Research groups that want a language model grounded in their own literature face a choice between hosted services that receive their unpublished work and self-hosted deployments that keep the data local but give the model no access to the corpus.1
• On 199 paired literature questions, the harness more than doubles the accuracy of the base model, from 0.387 to 0.874 (+0.487, 95% CI [0.407, 0.568]), while naive retrieve-then-answer scores below the unaided model on every backbone tested.1
• When the source paper for a question is removed from the corpus, the system abstains on about nine in ten of the questions it had answered correctly on the Qwen backbones and eight in ten on gpt-oss-20b, and it produces no fabricated local citation across 300 fabricated references.1
• With all outbound network access disabled, both Qwen backbones still exceed the published PaperQA2 accuracy.1

Sources (1)

• [1]MuninAI: A Self-Hosted Agentic Framework for Independent Research Groups
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 01:56 PM

  Munin is an open-source framework for a self-hosted scientific assistant that indexes a group's corpus and its citation graph, and wraps whichever open-weight model the group can serve in an agent harness with specialised reading, search, and computation tools.

  Research groups that want a language model grounded in their own literature face a choice between hosted services that receive their unpublished work and self-hosted deployments that keep the data local but give the model no access to the corpus.

Extractive summary: sentences quoted from the sources.