CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference
arXiv stat.ML5d4 min read
arXiv:2607.22511v1 Announce Type: new Abstract: Automating theoretical research is constrained not only by the generation of candidate results, but also by their reliable evaluation. A common approach is to close the research loop with a large language model (LLM) reviewer. However, such reviewers remain empirically unreliable: they may accept fabricated papers and detect them at rates close to chance (Bad Scientist, 2025). We present CausalForge, a framework for automated theoretical research in causal inference grounded in the Lean proof assistant. CausalForge combines Causalean, a foundatio