ludwigw/causal-reasoning-benchmarks
收藏Hugging Face2026-03-19 更新2026-03-29 收录
下载链接：
https://hf-mirror.com/datasets/ludwigw/causal-reasoning-benchmarks
下载链接
链接失效反馈官方服务：
资源简介：
---
license: mit
task_categories:
- text-classification
language:
- en
tags:
- causal-reasoning
- transitivity
- d-separation
- axiomatic-training
- semantic-loss
pretty_name: Causal Reasoning Benchmarks
size_categories:
- 10K<n<100K
---
# Causal Reasoning Benchmarks
Datasets used in "On Semantic Loss Fine-Tuning Approach for Preventing Model Collapse in Causal Reasoning" (Deshmukh & Gupta, 2026).
## Dataset Structure
- `train/transitivity_train.jsonl` — 50,000 transitivity training examples
- `train/dsep_train.jsonl` — 50,000 d-separation training examples
- `eval/length_eval.jsonl` — 10,000 length generalization examples
- `eval/branching_eval.jsonl` — 10,000 branching structure examples
- `eval/reversed_eval.jsonl` — 10,000 reversed edge examples
- `eval/shuffled_eval.jsonl` — 10,000 shuffled premise examples
- `eval/long_names_eval.jsonl` — 10,000 long node name examples
## Data Format
Each JSONL line:
```json
{"premise": "A causes B. B causes C.", "hypothesis": "Does A cause C?", "label": "Yes"}
```
## Citation
```bibtex
@article{deshmukh2026semantic,
title={On Semantic Loss Fine-Tuning Approach for Preventing Model Collapse in Causal Reasoning},
author={Deshmukh, Pratik and Gupta, Atirek},
year={2026}
}
```
提供机构：
ludwigw
