22 research outputs found

    Humanity's Last Exam

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    Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

    Barbielat: Codes and slides for Generate Your L(AI)brary Hackathon

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    # SMU Libraries GPTSMU Libraries GPT is a web-based application that can be deployed using Streamlit (currently not publicly deployed due to keeping the API key a secret) that takes in user prompts and uses LangChain with OpenAI to generate answers.https://github.com/robinsjules/AI-Chatbot/assets/111500254/cec2065e-3488-46c0-96c5-c7296eeb7179## Features- Intelligent Recommendation: Users can describe their interests or conditions to receive a more personalised answer.- Q&A Search Enginge: Based on our dataset, the chatbot can provide direct answers to FAQ.## DeploymentTo deploy the project locally, make sure to:- Put your own OpenAI API key in the constants.py file- Download and open the project folder, then type 'streamlit run app.py' in the terminal- Open [http://localhost:8501](http://localhost:8501) using your browser to see the project- Simply input your prompts in the text box to receive an answer!</p
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