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I created an AI assistant to help me read papers quickly. 1. Open AK 's daily paper recommendations 2. Screenshot the first page of the paper 3. Paste the image into the AI assistant and generate a summary The assistant: Watch the demo video 👇

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Jiayuan (JY) Zhang

107,287 subscribers

24,095 görüntüleme • 3 yıl önce •via X (Twitter)

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Daily paper recommendations

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Coral AI News2 yıl önce

Coral AI is the most powerful AI for documents. See the difference yourself:

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Hayo3 yıl önce

Thank you so much for sharing! The AI assistant you've created is truly fantastic, allowing you to quickly go through research papers is incredibly practical. Your innovation not only boosts efficiency but also provides a valuable tool for others. Your creativity is commendable, and it's benefiting many.

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Scite Assistant now lets you chat with any research papers even if they are paywalled. Go to scite(dot)ai and click on Assistant. In Scite Assistant, click on "Sources" and type the title of the research paper you want to chat with. You can add multiple papers. Now when you ask a question, Scite Assistant will reply with reference to the papers you added.
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Scite Assistant now lets you chat with any research papers even if they are paywalled. Go to scite(dot)ai and click on Assistant. In Scite Assistant, click on "Sources" and type the title of the research paper you want to chat with. You can add multiple papers. Now when you ask a question, Scite Assistant will reply with reference to the papers you added.

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1. SciSpace Copilot An AI assistant that explains papers in real-time. Highlight the text to understand it better, understand formulas and tables, and ask papers anything.
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1. SciSpace Copilot An AI assistant that explains papers in real-time. Highlight the text to understand it better, understand formulas and tables, and ask papers anything.

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How to extract data from papers for literature review in seconds? 1. Go to 2. Upload 2-3 papers you already know are relevant 3. Start with clicking on one paper 4. ResearchCollab do the following for the paper ✦ Provide a short overview of the paper ✦ Identify weaknesses in the paper ✦ Share papers that contrast the existing paper ✦ Extract meta data about the paper ✦ Evaluate each part (e.g., methodology) of the paper ✦ Provide AI chat to extract any other data 5. Now click on the Related Papers button at top right 6. You will get papers related to the seed paper 7. You can click on each paper and read its abstract 8. If you find it relevant, just add it to your list of papers 9. Do the same for the other 2 seed papers 10. This way you will collect all relevant papers 11. And extract data from those papers After this, analyse the data and report the findings. Try ResearchCollab today:
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How to extract data from papers for literature review in seconds? 1. Go to 2. Upload 2-3 papers you already know are relevant 3. Start with clicking on one paper 4. ResearchCollab do the following for the paper ✦ Provide a short overview of the paper ✦ Identify weaknesses in the paper ✦ Share papers that contrast the existing paper ✦ Extract meta data about the paper ✦ Evaluate each part (e.g., methodology) of the paper ✦ Provide AI chat to extract any other data 5. Now click on the Related Papers button at top right 6. You will get papers related to the seed paper 7. You can click on each paper and read its abstract 8. If you find it relevant, just add it to your list of papers 9. Do the same for the other 2 seed papers 10. This way you will collect all relevant papers 11. And extract data from those papers After this, analyse the data and report the findings. Try ResearchCollab today:

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1. Microsoft announced Windows Co-Pilot. Bing Chat will be integrated into all your Windows apps to provide you with a centralized AI assistant. Windows 11 will become the first Operating System to adopt a centralized AI assistant to help you get things done.
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Introducing 11ai - the AI personal assistant that's voice-first and supports MCP. This is an experiment to show the potential of Conversational AI: 1. Plan your day and add your tasks to Notion 2. Use Perplexity to research a customer 3. Search and create Linear issues

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