One Minute NLP

One Minute NLP

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In-context learning
In-context learning is a prompting technique that allows LLMs to learn and adapt to new tasks based on examples provided within the input prompt…
 • Dasha Herrmannova
Reflection agents
Reflection is a simple but powerful technique for improving the quality of LLM responses by prompting the LLM to reflect on its own output to identify…
 • Dasha Herrmannova
Top-k and top-p sampling
Top-k and top-p sampling are methods used to control the randomness and diversity of LLM outputs.
 • Dasha Herrmannova
Reasoning Models
Reasoning models are a new class of LLMs designed to solve complex problems like math and coding.
 • Dasha Herrmannova
Group Relative Policy Optimization
Group Relative Policy Optimization (GRPO) is a reinforcement learning algorithm that was used to train DeepSeek-R1.
 • Dasha Herrmannova
Proximal Policy Optimization
Proximal Policy Optimization is frequently used in Reinforcement Learning from Human Feedback to further train LLMs after supervised fine-tuning. It was…
 • Dasha Herrmannova
RLHF
Reinforcement Learning from Human Feedback is a training phase used on LLMs after supervised fine-tuning to further improve LLM responses. It was one of…
 • Dasha Herrmannova
One Minute NLP
One Minute NLP
Every week, I break down one key NLP/Generative AI concept into a single, easy-to-digest slide so you can stay on top of the field in just one minute a week.
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