The automated approach leverages the cross-combination of high-quality papers from top conferences to uncover feasible research and innovation ideas. Through multi-level verification and convergence screening, it identifies research schemes that are feasible and have in-depth value.

A curated guide for LLM-agent-driven scientific research automation — from getting started to the frontier.

Sub-Process Orchestration - Human problem-solving, complex systems (10-stage pipeline)

Methods and reviewer workflows for detecting AI-generated issues in scientific manuscripts.

Check whether AI-assisted R&D work is truly verified progress. Local-first LOSCR implementation with JSONL evidence ledgers, deterministic replay, service control, and claim checking.

Code for the paper: "Automatic Evaluation Metrics for Artificially Generated Scientific Research" (https://arxiv.org/abs/2503.05712)