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    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    the pursuit of*Self-correction during thought process:*The user wants a concise explanation (3-20 words) of what the neuron detects or predicts by finding patterns in lists. The explanation should be specific and avoid introductory phrases like "This neuron detects".Let's re-evaluate.MAX_ACTIVATING_TOKENS: `ti`, `'`, `the`, `two`, `the`, `’`, `<start_of_turn>`, `<start_of_turn>`TOKENS_AFTER_MAX_ACTIVATING_TOKEN: `gan`, `s`, `pursuit`, `close`, `plate`, `s`, `user`, `user`The most direct and repeated pattern seems to involve common preceding tokens followed by specific content.- ' `the` ' is followed by ' `pursuit` ' or ' `plate` '.- ' `two` ' is followed by ' `close` '.- ' `'`/'`’` ' is followed by ' `s` ' (possessive).- ' `<start_of_turn>` ' is followed by ' `user` '.The `TOP_POSITIVE_LOGITS` and `TOP_ACTIVATING_TEXTS` provide context.`TOP_ACTIVATING_TEXTS` mention: Sullivan, Queenan, Costello, pursuit of meaning, two close families, stepping up to the plate.`TOP_POSITIVE_LOGITS` include: `UrlResolution`, `makeText`, `BooleanField` (technical/programming terms), `Meksiku`, `surla` (less clear).The prompt specifically asks to find patterns in lists and explain the neuron's behavior based on those patterns. The initial thought of "the pursuit of" comes from `the` followed by `pursuit`. This is a strong candidate if we focus on direct token sequences.Let's think about other possibilities from the lists:- Possessives: `'s` (`'` -> `s`)- Proper nouns: "Sullivan", "Queenan", "Costello"- Descriptions: "two close families", "pursuit of what it means to you", "stepping up to the plate"The prompt emphasizes "finding patterns in lists" and "tokens following or preceding certain tokens".Looking again at `MAX_ACTIVATING_TOKENS` and `TOKENS_AFTER_MAX_ACTIVATING_TOKEN`:- `the` -> `pursuit` (`TOP_ACTIVATING_TEXTS`: "the pursuit of what it means to you") - Strong.- `two` -> `close` (`TOP_ACTIVATING_TEXTS`: "two close families") - Strong.- `'` / `’` -> `s` (`TOP_ACTIVATING_TEXTS`: "Queenan's") - Strong for possessives.- `<start_of_turn>` -> `user` (`TOP_ACTIVATING_TEXTS`: "<start_of_turn>user") - Strong for user turns.The neuron seems to activate when specific common tokens precede more descriptive or meaningful tokens.The word `the` appears twice in `MAX_ACTIVATING_TOKENS` followed by `pursuit` and `plate` in `TOKENS_AFTER_MAX_ACTIVATING_TOKEN`.`the pursuit` and `the plate` are very strong candidates. "the pursuit of" is a very common phrase initiator.What if the neuron is detecting phrases starting with "the" followed by a noun that is often part of a common idiom or significant phrase?- "the pursuit of"- "the plate" (stepping up to the plate)The prompt asks for "what the neuron detects or predicts by finding patterns in lists".The pattern 'the' followed by 'pursuit' or 'plate' is present."the pursuit of" is 3 words."the pursuit" is 2 words."the plate" is 2 words.Let's consider the `TOP_POSITIVE_LOGITS`: `surla`, `Meksiku`, `PMailer`, `ItemBackground`, `UrlResolution`, `snippetHide`, `makeText`, `Pind`, `bolista`, `BooleanField`. These are heavily technical.However, sometimes the context tokens (MAX_ACTIVATING_TOKENS/TOKENS_AFTER_MAX_ACTIVATING_TOKEN) are more general, and the text/logits provide specific examples of what that general trigger connects to.The key seems to be "finding patterns in lists".The pattern: `the` followed by `pursuit` or `plate`.If the neuron is about "the pursuit of", this is 3 words.If it's about "the plate", it's 2 words.If it's just "pursuit", it's specific.If it's "plate", it's specific.The `TOP_POSITIVE_LOGITS` are not very helpful in creating a simple phrase based on the token lists. Let's stick to the token lists' direct patterns.The phrase "the pursuit of" seems to be the most prominent pattern from `the` -> `pursuit` as seen in the `TOP_ACTIVATING_TEXTS`.It fits the 3-20 word constraint.It's a phrase, not a single word.It's specific.Let's check other possibilities:- `two close`: "two close families". This is also a pattern.- `'s`, `’s`: possessives.The instruction states "a majority should" match.`the` -> `pursuit` (exact match in text)`two` -> `close` (exact match in text)`'` -> `s` (exact match in text)`<start_of_turn>` -> `user` (exact match in text)Which pattern is strongest or most indicative?The `TOP_POSITIVE_LOGITS` are rather technical. This suggests the neuron might be involved in parsing structured text or code, or identifying specific types of phrases in general text that

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 20-gemmascope-res-131k
    Configuration
    google/gemma-scope-9b-it-res/layer_20/width_131k/average_l0_81
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    131,072
    Data Type
    float32
    Hook Name
    blocks.20.hook_resid_post
    Hook Layer
    20
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     étoit
    -0.59
     varandra
    -0.45
     مرئيه
    -0.44
     pouvoit
    -0.43
     lavable
    -0.42
     mixta
    -0.41
     auroit
    -0.41
     trône
    -0.39
     cenário
    -0.39
     illustrazione
    -0.39
    POSITIVE LOGITS
     surla
    0.50
     Meksiku
    0.43
    PMailer
    0.41
    ItemBackground
    0.41
    UrlResolution
    0.41
     snippetHide
    0.41
    makeText
    0.40
     Pind
    0.39
    bolista
    0.39
    BooleanField
    0.38
    Activations Density 0.067%

    No Known Activations