Arguinas: Argument Reconstruction Data for Supervising LLM Critical Thinking

The Arguinas dataset, created by researchers from Carnegie Mellon University and KAIST, is designed for argument reconstruction as a supervision method for critical thinking in large language models. It was uploaded to Hugging Face on April 20, 2026. The dataset is associated with the paper 'Argument Reconstruction as Supervision for Critical Thinking in LLMs'.

Use Cases

• Training LLMs for argument reconstruction based on the described supervision method.
• Benchmarking LLM performance on critical thinking tasks based on the dataset's purpose.
• Developing new supervision techniques for reasoning in AI systems based on the described research.

Strengths

• Dataset is associated with a specific research paper from institutions including Carnegie Mellon University and KAIST.
• Last updated on April 20, 2026, indicating recent availability.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Hugging Face, uploaded by author 'ChuGyouk'.

Collection Method

Likely created as part of the research described in the associated paper.

Time Range

Creation date is not specified; upload date is 2026-04-20.

Freshness

Last updated 2026-04-20 12:00:33; freshness should be verified.

Geography

Research involved institutions in the United States (Carnegie Mellon University) and South Korea (KAIST).