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README.md
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---
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task_categories:
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- text-retrieval
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language:
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- en
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pretty_name: Arxiv Search Index (From Semantic Scholar dump of August 1, 2024)
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size_categories:
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- 100M<n<1B
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---
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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
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This index is compatible with WikiChat v2.0.
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Refer to the following for more information:
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GitHub repository: https://github.com/stanford-oval/WikiChat
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Papers:
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- [WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia](https://arxiv.org/abs/2305.14292)
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- [SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsing](https://arxiv.org/abs/2406.00562)
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<p align="center">
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<img src="https://github.com/stanford-oval/WikiChat/blob/main/public/logo_light.png?raw=true" width="100px" alt="WikiChat Logo" />
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<h1 align="center">
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<b>WikiChat</b>
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<br>
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<a href="https://github.com/stanford-oval/WikiChat/stargazers">
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<img src="https://img.shields.io/github/stars/stanford-oval/WikiChat?style=social" alt="Github Stars">
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</a>
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</h1>
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</p>
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<p align="center">
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Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia
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</p>
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<p align="center">
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Online demo:
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<a href="https://wikichat.genie.stanford.edu" target="_blank">
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https://wikichat.genie.stanford.edu
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</a>
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<br>
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</p>
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<p align="center">
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<img src="https://raw.githubusercontent.com/stanford-oval/WikiChat/ee25ff7d355c8fbb1321489e1e955be8ae068367/public/pipeline.svg" width="700px" alt="WikiChat Pipeline" />
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</p>
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