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Finding the Words to Say: Hidden State Visualizations for Language Models

Named practitioner synthesis

#247

T3digested
Topic
Translation NLP
First seen
2026-07-16 19:08:00
Last seen
2026-07-16 19:08:00

Source raw items (1)

  • Blog / Newsletter2026-07-16 19:07:22
    Finding the Words to Say: Hidden State Visualizations for Language Models

    By visualizing the hidden state between a model's layers, we can get some clues as to the model's "thought process". Figure: Finding the words to say After a language model generates a sentence, we can visualize a view of how the model came by each word (column). Each row is a model layer. The value and color indicate the ranking of the output token at that layer. The darker the color, the higher the ranking. Layer 0 is at the top. Layer 47 is at the bottom. Model:GPT2-XL Part 2: Continuing the pursuit of making Transformer language models more transparent, this article showcases a collection of visualizations to uncover mechanics of language generation inside a pre-trained language model. These visualizations are all created using Ecco, the open-source package we're releasing In the first part of this series, Interfaces for Explaining Transformer Language Models, we showcased interactive interfaces for input saliency and neuron activations. In this article, we will focus on the hidden