datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
reasoning-chain-dependency-integrity-v0.1
What this dataset tests
Whether each step in a reasoning chain properly depends on prior steps.
The chain itself is the object.
Not the final answer.
Why this exists
Models often reach correct conclusions using:
skipped premises
reordered logic
circular justification
post-hoc explanations
This dataset isolates those failures.
Data format
Each row contains:
premises
reasoning_steps
dependency_graph
claimed_conclusion
The dependency graph… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/reasoning-chain-dependency-integrity-v0.1.clinical-evidence-dependency-graph-reasoning-v0.1
Clinical Multi-Evidence State Integration v0.1
Overview
Clinical Multi-Evidence State Integration v0.1 is a structured clinical-reasoning benchmark designed to test whether an AI system can integrate multiple sequential evidence events into a coherent final clinical state.
The benchmark evaluates more than final-answer classification.
A system must determine:
how each evidence event affects each tracked clinical item;
whether an item should be confirmed… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-evidence-dependency-graph-reasoning-v0.1.