language:it license:llama3 size_categories:10K<n<100K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars arxiv:2501.05032 region:us
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language:
- it
license: llama3
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<p align="center">
  🤗 <a href="https://huggingface.co/collections/HumanLLMs">Models</a> | 📊 <a href="https://huggingface.co/datasets/HumanLLMs/Human-Like-DPO-Dataset">Dataset</a> | 📄 <a href="https://arxiv.org/abs/2501.05032">Paper</a>
</p>

# **Human-Like-DPO-Dataset**

This dataset was created as part of research aimed at improving conversational fluency and engagement in large language models. It is suitable for formats like **Direct Preference Optimization (DPO)** to guide models toward generating more human-like responses.

The dataset includes **10,884 samples** across **256 topics**, including:

- Technology
- Daily Life
- Science
- History
- Arts

Each sample contains:
- **Conversational Question**: Natural, engaging questions that reflect everyday human dialogue.
- **Human-Like Response**: A natural, conversational answer generated to mimic human interaction.
- **Formal Response**: A structured, professional answer reflecting traditional AI responses.

# **Dataset Usage**
This dataset can be used to fine-tune LLMs to:
- Improve conversational coherence.
- Reduce mechanical or impersonal responses.
- Enhance emotional intelligence in dialogue systems.

More details on dataset creation and usage can be found in the accompanying [research paper](https://arxiv.org/abs/2501.05032).