Today on the blog, read all about symbol tuning, a method that fine-tunes models on tasks where natural language labels are replaced with arbitrary symbols. Learn how symbol tuning can improve in-context learning for benefits across various settings →
https://
goo.gle/3rt3r8U
MACHINE LEARNING
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Symbol Tuning: Improving In-Context Learning with Arbitrary Symbols
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Mode Collapse in LLMs: Understanding Model Degradation
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This is an example of mode collapse—which it turns out happens in LLMs as well (and we discuss in the paper)!
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AI Models Data Generation Distribution Guarantees
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Despite growing interest in using these models to generate data, there are currently no guarantees about the resulting distribution. For example, if I want a normal distribution, it would look like this:
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LLMs Generate Synthetic Data: New Research Released
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As part of my takeover, I’ll (
@aspenkhopkins
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Sequence Packing Applied to Image Patches – Novel Approach
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So, basically sequence packing but for image patches. Neat. And surprised no one has tried that yet
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Changing Opinion After Reading a Research Paper
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No I first was and then I wasn’t when I saw that paper and all the congrats in the replies . (How do we expect LLMs to ever solve text comprehension)
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KNN Classification Works Through Majority Vote Among Neighbors
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Yes, I assume this should work because the compute the label based on majority vote among the nearest neighbors.
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Transfer Learning: Leveraging Pre-trained Models for Specialized AI
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Ever since the availability of pre-trained models, transfer learning has always been used to make more specialized models. What Is AI Transfer Learning and How Does It Work? https://
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Data Scientists Face Overwhelming Information Challenges Daily
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The world is dealing with more data every day. We know #DataScientists are overwhelmed, and we hear you. What's the biggest challenge with today's state of too much information?
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Next Generation Enterprise AI Combines Generative and Classical ML
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"What’s the next generation of enterprise #AI going to look like? If you ask DataRobot CEO Debanjan Saha, enterprises will see the most business benefits by combining new generative AI tools and techniques with the classical AI and machine learning approaches that customers have