---
task_categories:
- text-retrieval
language:
- en
pretty_name: Arxiv Search Index (From Semantic Scholar dump of August 1, 2024)
size_categories:
- 100M<n<1B
---
This repository contains a Qdrant index created from preprocessed and chunked arxiv papers from [Semantic Scholar](https://api.semanticscholar.org/api-docs/datasets). The embedding model used is [Alibaba-NLP/gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5).

This index is compatible with WikiChat v2.0.
Refer to the following for more information:

GitHub repository: https://github.com/stanford-oval/WikiChat

Papers:
- [WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia](https://arxiv.org/abs/2305.14292)
- [SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsing](https://arxiv.org/abs/2406.00562)

<p align="center">
    <img src="https://github.com/stanford-oval/WikiChat/blob/main/public/logo_light.png?raw=true" width="100px" alt="WikiChat Logo" />
    <h1 align="center">
        <b>WikiChat</b>
        <br>
        <a href="https://github.com/stanford-oval/WikiChat/stargazers">
            <img src="https://img.shields.io/github/stars/stanford-oval/WikiChat?style=social" alt="Github Stars">
        </a>
    </h1>
</p>
<p align="center">
    Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia
</p>
<p align="center">
    Online demo:
    <a href="https://wikichat.genie.stanford.edu" target="_blank">
        https://wikichat.genie.stanford.edu
    </a>
    <br>
</p>

<p align="center">
    <img src="https://raw.githubusercontent.com/stanford-oval/WikiChat/ee25ff7d355c8fbb1321489e1e955be8ae068367/public/pipeline.svg" width="700px" alt="WikiChat Pipeline" />
</p>