Neuron Explorer

Qwen3-0.6B

'Latin' in word origin notes

A neuron in layer 10 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron lights up on the word 'Latin' (and nearby commas) in dictionary-style word origin notes, such as 'from Latin' or 'Middle English'. It goes negative on words in math and engineering text, like 'solution' or 'analytically'. Turning it up did not bring out a word-origin theme in the model's writing.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    strontianite⏎- Named in a pseudo-Latin manner for the name of the Scottish town Strontian. (Wiktionary)⏎- From New Latin strontia, strontium oxide, from English strontian; see

  2. #2 peak

    more fragrant sauce⏎- black, green or white pepper – for some sharpness⏎- nutmeg – a popular addition in many<|endoftext|>From Latin: arcus "a bow, arch,"⏎Try this Drag one of the orange

  3. #3 peak

    ) of praktikos (see practical); the noun from the verb within the earlier spelling practise, on the sample of pairs akin to advise, recommendation.⏎Word Origin Middle English (in legal<|endoftext|>Keywords: Sargent Mountain⏎Historical Items Showing

  4. #4 peak

    Origin late Middle English: from Latin attentio(n-), from the verb attendere (see attend). Nonetheless,

  5. #5 peak

    lia, from Latin, neuter pl. of rēgālis, regal⏎An explanation

  6. #6 peak

    with thyroid conditions have a higher risk of getting caught in this endless “more stress – more hormonal disbalance” circle.⏎That is why<|endoftext|>Manufacturing (from Latin manu factura, "making by hand") is the use of tools and labor

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

turned down a lot
Prompt

Here is something I have been thinking about lately: I have a function that is a function of time, and I am going to take the derivative of the function to find the derivative, which is a complex and beautiful result. Let's call it $ f $, which is the derivative of

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    circular and windings are modeled as current sheets placed on the core surface. The induction machine geometry is shown in Figure 2. Poisson’s equation is solved analytically for geometry and temperature as shown in Figure 3. The results

  2. #2 peak

    somewhat disparate. The process is illustrated using a single, simple differential equation:⏎Integrate this equation from t = 0 to t = 1. The exact solution can be found by quadrature and is⏎To use MATLAB we first construct an

  3. #3 peak

    the private market equilibrium socially efficient from the viewpoint of a social planner that seeks to maximize the representative consumers utility function ? Explain why or why not, by analyzing the solution to for c and k in the

  4. #4 peak

    ators.⏎- Allow them to discover how each is related to the value of the common ratio and the sign of the first term.⏎- Have them develop an explicit formula for each sequence.⏎2. A company is offering to pay you one penny on

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L6:789 excites
  2. L9:41 excites
  3. L6:1147 excites
  4. L8:3011 suppresses
  5. L6:1164 suppresses
  6. L8:1189 suppresses
  7. L9:683 excites
  8. L7:1885 weakly suppresses
  9. L9:1692 weakly excites
  10. L9:86 weakly excites
  11. L9:728 weakly suppresses
  12. L6:1488 weakly suppresses
  13. L7:2789 weakly suppresses
  14. L9:470 weakly suppresses
  15. L9:569 weakly excites
  16. L6:2841 weakly suppresses
  17. L8:1555 weakly excites
  18. L8:1548 weakly excites
  19. L9:117 weakly excites
  20. L9:1650 weakly excites
  21. L2:1667 weakly excites
  22. L7:2022 weakly excites
  23. L9:1824 weakly excites
  24. L7:1195 weakly excites

Feeds later layers

  1. L17:1349 suppresses
  2. L17:951 suppresses
  3. L15:1850 suppresses
  4. L11:1829 suppresses
  5. L11:420 excites
  6. L23:339 suppresses
  7. L19:2721 suppresses
  8. L11:549 suppresses
  9. L11:743 suppresses
  10. L18:2200 suppresses
  11. L17:2576 suppresses
  12. L13:1055 suppresses
  13. L11:1106 excites
  14. L21:1633 suppresses
  15. L11:828 suppresses
  16. L23:410 suppresses
  17. L13:1455 suppresses
  18. L18:1282 suppresses
  19. L21:585 suppresses
  20. L11:2330 suppresses
  21. L11:602 suppresses
  22. L19:1821 weakly suppresses
  23. L11:2185 weakly suppresses
  24. L20:1545 weakly suppresses

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

1 values between -2.04 and -1.971 values between -1.97 and -1.901 values between -0.97 and -0.901 values between -0.61 and -0.541 values between -0.54 and -0.472 values between -0.47 and -0.396 values between -0.39 and -0.3211 values between -0.32 and -0.2560 values between -0.25 and -0.18148 values between -0.18 and -0.11446 values between -0.11 and -0.041016 values between -0.04 and 0.041044 values between 0.04 and 0.11631 values between 0.11 and 0.18315 values between 0.18 and 0.25138 values between 0.25 and 0.3249 values between 0.32 and 0.4019 values between 0.40 and 0.477 values between 0.47 and 0.545 values between 0.54 and 0.613 values between 0.61 and 0.682 values between 0.68 and 0.751 values between 0.75 and 0.83offnegativepositiveoften

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.

Promotes

  1. anks
  2. 逢
  3. 选手
  4. _scores
  5. icks
  6. Scores
  7. ocols
  8. vals
  9. 贰
  10. ographics

Suppresses

  1. logically
  2. rewritten
  3. analy
  4. quadratic
  5. Equation
  6. pler
  7. predict
  8. predict
  9. equation
  10. fourth