xjh111/nanoresearch-20topics

NanoResearch 20 Topics

This dataset contains 20 research-task specifications used to evaluate NanoResearch across multiple machine-learning domains. Each example describes a compact research problem, expected baselines, datasets, and user-facing requirements for generating an implementation-oriented research plan.

Schema

Each record contains:

• —question_id: unique task identifier.
• —domain: research domain, such as NLP, CV, Tabular ML, Time Series, Graph ML, Audio, or Multimodal.
• —difficulty: coarse difficulty category.
• —background: context motivating the task.
• —problem_statement: target research problem.
• —baselines: baseline methods to consider.
• —datasets: datasets associated with the task.
• —user_requirements: user-facing constraints and expected output style.
• —extra_context: additional implementation or evaluation constraints.

Usage

from datasets import load_dataset

ds = load_dataset("xjh111/nanoresearch-20topics", data_files="data/nanoresearch_20topics.json")
print(ds["train"][0])

Citation

If you use this dataset, please cite the NanoResearch project or paper associated with this benchmark.