The Epistemic Curie Benchmark (ECB) measures when large language models surrender independent reasoning. Created by Sardor Razikov and updated in April 2026, it is a dataset for evaluating AI behavior. The dataset and accompanying code are available on HuggingFace.
Use Cases
- Evaluating LLM compliance thresholds based on the described sigmoid curve.
- Benchmarking model behavior in epistemic reasoning scenarios.
- Studying the surrender of independent reasoning in AI systems.
Strengths
- Dataset is associated with a published paper (DOI: 10.5281/zenodo.19791329).
- A version update was made in April 2026 to refine the theoretical framing.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Author ZeroR3 on HuggingFace.
- Freshness
- Last updated 2026-04-29 09:48:32