RyanSaklad/ReCITE
ReCITE: Real-world CausalIty from Textual Evidence Benchmark ReCITE (Real-world CausalIty from Textual Evidence) is a benchmark for evaluating LLMs on causal graph extraction from real-world scientific text. It contains 292 annotated causal graphs from open-access MDPI and PLOS articles spanning diverse OpenAlex fields. Paper: Can Large Language Models Infer Causal Relationships from Real-World Text? GitHub: ReCITE Repository Dataset Configurations This dataset… See the full description on the dataset page: https://huggingface.co/datasets/RyanSaklad/ReCITE.
| Author / organization | RyanSaklad |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 477 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 5 December 2025 |
| Last updated at source | 25 January 2026 |
Recent changes
- 16 Oct 2026 Description: ReCITE: Real-world CausalIty from Textual Evidence Benchmark ReCITE (Real-world CausalIty from Textual Evidence) is a benchmark for evaluating LLMs on causal graph extraction from real-world scientific text. It contains 292 annotated causal → ReCITE: Real-world CausalIty from Textual Evidence Benchmark ReCITE (Real-world CausalIty from Textual Evidence) is a benchmark for evaluating LLMs on causal graph extraction from real-world scientific text. It contains 292 annotated causal
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