Title: Large Language Models are not Fair Evaluators Affiliation(s): Peking University 、The University of Hong Kong 、Tencent Cloud AI Date:2023.06 Published In: Arxiv Abs:(1)文本发现,LLM存在严重的位置偏差为了解决这个问题。(2)本文提出了一个校准框架来减轻位置偏差,其中包含三个简单但有效的策略:...
Large language models are much more like discoveries. We’re constantly getting surprised by their capabilities. They’re not really engineered objects. The comment underscores the fact that there’s much even the engineers of large language models don’t understand about where generative AI ...
AI language models are transforming the medical writing space -- like it or not!doi:10.56012/qalb4466LANGUAGE modelsMEDICAL writingARTIFICIAL intelligenceWhether you're an early adopter, an occasional user, or yet to acknowledge its transformative potential, artificial intelligence (AI) --...
That’s kind of the concept of zero-shot learning with large language models. Foundation models are trained for wide application by not feeding them much in the way of how a task is done, in essence, giving them only limited training opportunities to form understanding while having an expectat...
Large language models are trained usingunsupervised learning. With unsupervised learning, models can find previously unknown patterns in data using unlabelled datasets. This also eliminates the need for extensive data labeling, which is one of the biggest challenges in building AI models. ...
OpenAI has not revealed much about how ChatGPT-4 was built. But a look at its predecessor, ChatGPT-3, is suggestive. Large language models (LLMs) are trained on text scraped from the internet, on which English is the lingua franca. Around 93% of ChatGPT-3’s training data was in En...
Training models with different activation functions improved explanation scores. We are open-sourcing our datasets and visualization tools for GPT‑4-written explanations of all 307,200 neurons in GPT‑2, as well as code for explanation and scoring using publicly available models(opens in a ...
How to detect AI-generated content The future of large language models The future of LLMs is still being written by the humans who are developing the technology, though there could be a future in which the LLMs write themselves, too. The next generation of LLMs will not likely be artifici...
As AI language models are rolled out into products and services used by millions of people, understanding their underlying political assumptions and biases could not be more important. That’s because they have the potential to cause real harm. A chatbot offering health-care advice might refuse to...
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