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    **Data Analysis for Neuron Behavior Explanation**My task is to distill the essence of this neuron's function into a concise phrase (3-20 words), identifying patterns from the provided lists without explicitly mentioning "tokens" or "patterns." I need to determine what this neuron 'detects' or 'predicts' by finding commonalities or sequence indicators.Here’s my analysis of each list:1. **MAX_ACTIVATING_TOKENS**: * `1` * `[` * `(` * `1` * `(` * `Timestamp` * `tensor` * `(` * `[` * `[` This list is dominated by structural elements like brackets `[` and parentheses `(`, numbers like `1`, and technical terms commonly found in code or data structures like `Timestamp` and `tensor`. It suggests a focus on parsing or recognizing structured data formats, possibly code-related or data representation.2. **TOKENS_AFTER_MAX_ACTIVATING_TOKEN**: * `0` * `Event` * `1` * `0` * `0` * `('` * `([` * `1` * `].` * `System` Following the structural tokens, we see numbers, the word `Event`, and the `System` namespace (often seen in programming contexts). The presence of `Event` is notable, especially in conjunction with programming-related tokens from the previous list. The `('` and `].` further reinforce a code-parsing context.3. **TOP_POSITIVE_LOGITS**: * `ousands` * `ateful` * `من` (Arabic for "of", "from") * `ese` * `illi` * `hundreds` * `千` (Chinese for "thousand") * `нашей` (Russian for "our") * `нашего` (Russian for "our") * `ESP` (Possibly part of 'especially' or a specific acronym) This list is quite diverse. It includes number-related terms like `thousands`, `hundreds`, and `千` (thousand). Crucially, it also contains words from multiple languages (`من`, `нашей`, `нашего`). This suggests the neuron might be sensitive to numerical quantities and potentially multilingual text or localization contexts. The presence of `ful` or `ful` endings (`-ateful`, `ousands` possibly from `thousands`) might indicate a focus on descriptive words or concepts.4. **TOP_ACTIVATING_TEXTS**: * `" Write a query in DSL to find the documents where name must be "ABC" and date must be between "10/12/2022" and "15/12/2022"<end_of_turn>` * `can you show me my calender output: ( Yield :output ( FindEventWrapperWithDefaults :constraint ( Constraint[Event] ) ) ) input: Hi, I need help checking my calender output: ( PleasantryCalendar` * `<start_of_turn>user Compute the norm of the vector (1/2, 1, 1)<end_of_turn> <start_of_turn>model Let the vector be $v = (\frac` * `. Now, begin! - Question: Find the documents where name is "ABC" and date between "10/12/2022" and "15/12/2022"<end_of_turn>` * `None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError(0, 'Error'))': /simple/pip/ WARNING: Retrying (Retry(total=3, connect` * `42080804488696, 'window_start_at': Timestamp('2023-05-14 00:00:00+000` * `# Perform an operation (executed immediately) z = x + y print(z) # Output: tensor([5., 7., 9.]) # Dynamic graph construction a = torch.randn(2,` * `<start_of_turn>user I have these two permutation cycles: (1,2,3),(3,4). How can I put them as disjointed cycles?<end_of_turn> <start_of_turn>model` * `AI who performs one task based on the following objective: Solve world hunger. Take into account these previously completed tasks: []. Your task: Develop a task list Response:<end_of_turn> <start_of_turn>model Okay, my objective is to solve` * `the first row to light blue Set-RowBackgroundColor -DataGridView $datagrid -RowIndex 0 -Color [System.Drawing.Color]::LightBlue # Example: Change the background color of the third row to light green` These examples are highly varied: * **DSL queries**: "query in DSL", finding documents with name and date ranges. * **Calendar/Event queries**: "show me my calender", "FindEventWrapperWithDefaults", `Constraint[Event]`. * **Mathematical/Computational Python code**: computing vector norms, `tensor`, `torch.randn`. * **System/Programming messages**: `ProxyError`, `WARNING`, `sys.path`. * **Structured data/timestamps**: `Timestamp('2023-05-14 00:00:00+000`. * **Algorithmic/combinatorial questions**: permutation cycles. * **Task-based AI instructions**: "Solve world hunger". * **Scripting commands**: `Set-RowBackgroundColor`.**Synthesizing the Pattern:**1. **Structure/Code Context**: `MAX_ACTIVATING_TOKENS` (`[`, `(`, `Timestamp`, `tensor`) strongly points to code, data structures, or structured queries. `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` (`Event`, `System`, `(`, `]`) reinforce this.2. **Numerical/Date Information**: Several examples involve dates ("10/12/2022"), numerical ranges, or numerical operations (vector norm). The `TOP_POSITIVE_LOGITS` also contain number-related words.3. **Multilingualism/Numbers**: `TOP_POSITIVE_LOGITS` includes words from Arabic, Chinese, and Russian, alongside English words for large numbers. This could

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
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    google/gemma-scope-2-27b-it/transcoder_all/layer_23_width_262k_l0_small_affine
    Prompts (Dashboard)
    238,145 prompts, 512 tokens each
    Dataset (Dashboard)
    lmsys + oasst1
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    Negative Logits
     analiz
    0.52
     cinematography
    0.46
     teorie
    0.43
     scienze
    0.43
     cinematographer
    0.42
     discours
    0.41
     videoj
    0.40
    کند
    0.40
     kinemat
    0.40
     episodi
    0.40
    POSITIVE LOGITS
    ousands
    0.45
    ateful
    0.40
     من
    0.39
    ese
    0.39
    illi
    0.38
     hundreds
    0.38
    千
    0.38
     нашей
    0.37
    ของเรา
    0.37
     ESP
    0.36
    Activations Density 0.038%

    No Known Activations