AI research workflow: from question to experiments and manuscript
AutoResearch connects literature exploration, testable ideas, model implementation, GPU experiments and manuscript drafting. Researchers can inspect the results and artifacts behind the work.
Current beta research areas include computer vision, time series, natural language processing, mechanical prognostics, battery health and structural health monitoring.
1. Define a question that can be tested
Start with a field, a concrete prediction or modeling task, and the evidence that would support your hypothesis. For battery health, for example, ask whether a method generalizes to operating conditions absent from training. AutoResearch helps explore literature and develop ideas; researchers still need to check novelty and source accuracy.
2. Prepare data and an evaluation plan
Record where the data comes from, which inputs are available at prediction time, and how training, validation and test sets are separated. Splitting by device, subject or time may be necessary to avoid leakage. Choose task-appropriate metrics and decide how to compare methods before looking at test results.
3. Implement models and fair baselines
Turn the research plan into code and establish relevant baselines. Keep preprocessing, splits and evaluation rules comparable. Record configurations and seeds so the proposed method and baselines can be examined under the same conditions. AutoResearch connects modeling and experiment preparation within the research workflow.
4. Run GPU experiments and inspect the evidence
Train and evaluate models on configured GPU resources. Inspect logs, returned files and comparisons. Use ablations to test which parts of a method matter; repeat runs when variation could change the conclusion. A completed run is evidence that code executed, not proof that the research claim is correct.
5. Build figures and a manuscript from actual results
Use the measured outputs for tables, figures and scientific claims. AutoResearch assists with manuscript drafting, review and revision. Check references, match every numerical claim to an experiment artifact, and describe failed experiments and limitations where relevant. No workflow can promise acceptance or a positive scientific result.
6. Review the work and apply for the beta
Before sharing or submitting, review the code, experimental design, source material and generated text. To apply, use the product homepage and describe your research direction. Access is reviewed by the administrator. The Chinese and English interfaces provide corresponding research workflows.
Questions before you start
Do I need a finished research idea?
No. You can begin with a broad direction and refine a testable question during planning.
Can the system guarantee a publishable paper?
No. Scientific value depends on the question, data, experimental evidence and expert review. Publication decisions remain with journals and conferences.
Is beta access immediate?
No. Submit an application on the homepage; access requires approval. Approved members receive 5,000 starter credits.