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--- |
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language: |
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- en |
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tags: |
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- glm |
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- webglm |
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- thudm |
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inference: false |
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--- |
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<h1>WebGLM: Towards An Efficient Web-enhanced Question Answering System with Human Preference</h1> |
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<p align="center"> |
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📃 <a href="https://arxiv.org/pdf/2306.07906.pdf" target="_blank">Paper (KDD 2023)</a> |
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💻 <a href="https://github.com/THUDM/WebGLM" target="_blank">Github Repo</a> |
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</p> |
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# Introduction |
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WebGLM-2B aspires to provide an efficient and cost-effective web-enhanced question-answering system using the 2-billion-parameter General Language Model (GLM). It aims to improve real-world application deployment by integrating web search and retrieval capabilities into the pre-trained language model. |
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WebGLM is built by the following parts: |
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- **LLM-augmented Retriever**: Enhances the retrieval of relevant web content to better aid in answering questions accurately. |
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- **Bootstrapped Generator**: Generates human-like responses to questions, leveraging the power of the GLM to provide refined answers. |
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- **Human Preference-aware Scorer**: Estimates the quality of generated responses by prioritizing human preferences, ensuring the system produces useful and engaging content. |
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This repo is the implementation of **Bootstrap Generator**. |
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See our [Github Repo](https://github.com/THUDM/WebGLM) for more detailed usage. |
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