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---
language:
- en
license: mit
size_categories:
- 10K<n<100K
task_categories:
- question-answering
- text-analysis
tags:
- knowledge-coupling
- llama2
- hotpotqa
- multi-hop-reasoning
- gradient-analysis
- ripple-effects
---
# Knowledge Coupling Analysis on HotpotQA Dataset
## Dataset Description
This dataset contains the results of a comprehensive knowledge coupling analysis performed on the HotpotQA dataset using LLaMA2-7B model. The analysis investigates how different pieces of knowledge interact within the model's parameter space through gradient-based coupling measurements.
## Research Overview
- **Model**: meta-llama/Llama-2-7b-hf (layers 28-31 focused analysis)
- **Dataset**: HotpotQA (train + dev splits, 97,852 total samples)
- **Method**: Gradient-based knowledge coupling via cosine similarity
- **Target Layers**: model.layers.28-31.mlp.down_proj (semantically rich layers)
## Key Findings
The analysis revealed:
- Mean coupling score: 0.0222 across all knowledge piece pairs
- High coupling pairs (≥0.4 threshold): Critical for ripple effect prediction
- Layer-specific analysis focusing on MLP down-projection layers
- Comprehensive gradient analysis with 180,355,072 dimensions per knowledge piece
## Files Description
### Core Results
- `global_analysis_results.json`: Comprehensive analysis summary with statistics
- `all_knowledge_pieces.json`: Complete set of processed knowledge pieces (92MB)
- `all_coupling_pairs.csv`: All pairwise coupling measurements (245MB)
### Supporting Files
- `dataset_info.json`: Dataset statistics and conversion details
- `coupling_analysis_config.json`: Analysis configuration and parameters
## Usage
```python
from datasets import load_dataset
# Load the knowledge coupling results
dataset = load_dataset("your-username/hotpotqa-knowledge-coupling")
# Access global analysis results
global_results = dataset["global_analysis"]
# Access knowledge pieces
knowledge_pieces = dataset["knowledge_pieces"]
# Access coupling pairs
coupling_pairs = dataset["coupling_pairs"]
```
## Citation
If you use this dataset in your research, please cite:
```bibtex
@dataset{hotpotqa_knowledge_coupling,
title={Knowledge Coupling Analysis on HotpotQA Dataset using LLaMA2-7B},
author={[Your Name]},
year={2024},
publisher={HuggingFace},
url={https://huggingface.co/datasets/your-username/hotpotqa-knowledge-coupling}
}
```
## Technical Details
- **Gradient Computation**: ∇_θ log P(answer|question) for cloze-style questions
- **Coupling Measurement**: Cosine similarity between L2-normalized gradients
- **Memory Optimization**: Focused on layers 28-31 to handle GPU memory constraints
- **Hardware**: NVIDIA A40 GPU (46GB VRAM)
## License
This dataset is released under the MIT License. The original HotpotQA dataset follows its respective licensing terms.
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