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LLM Behavioral Research · Active

Multi-Agent Research Pipeline

A reusable scaffold of four specialized LLM agents — Lead Contributor, Positioning, Method, and Experiment owners — that collaborate to draft, review, and assemble a research paper end-to-end.

Multi-agent Research automation LaTeX Tool use

A workflow we use across our own research projects: each role is an LLM-backed agent with a fixed set of skills (define structure, narrative synthesis, write intro, review & merge, consistency check, LaTeX final assembly, version control). Shared skills like academic search, latex assembly, and assistant-text extraction live in a sibling shared_skills/ package.

Why agents per role, not per task

A single mega-agent loses coherence across long sections; one agent per role preserves voice, lets us prompt-engineer per-section conventions (notation, citation density, evidence standards), and gives us a clean ownership signal for review and version control.

Where it ships

  • dcn_v2_agents/ — used to produce our DCN-V2 paper.
  • llm_bias_agents/ — used to produce our LLM bias paper, with the same four-role structure and additional benchmark/validation skills.

The pipeline is being generalized into a standalone library so future EIL projects can scaffold a paper workflow in one command.