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    3. Apollo Research · Taylor · Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
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    9. 6-RES_SCL-AJT
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    text related to military action and armored equipment

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    neuronpedia/gpt2-small__res_scl-ajt/6-res_scl-ajt
    Prompts (Dashboard)
    12,288 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    46,080
    Data Type
    torch.float32
    Hook Point
    blocks.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    apollo-research/Skylion007-openwebtext-tokenizer-gpt2
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Neuron Alignment
    Index
    Value
    % of L₁
    566
    +0.10
    0.6%
    450
    +0.10
    0.6%
    554
    +0.09
    0.5%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    288
    +0.10
    0.23
    326
    +0.10
    0.22
    99
    +0.09
    0.09
    Negative Logits
    yip
    -0.70
    ãĤ§
    -0.67
    ãĤ´ãĥ³
    -0.59
    bread
    -0.55
    astrous
    -0.55
    uation
    -0.54
    çīĪ
    -0.53
    ples
    -0.53
    uity
    -0.53
    eteenth
    -0.51
    POSITIVE LOGITS
     maneuvers
    0.60
     personnel
    0.57
     vehicles
    0.55
    retch
    0.54
     Amph
    0.53
     trucks
    0.53
    merga
    0.52
    rity
    0.52
    naires
    0.52
     armoured
    0.52
    Activations Density 8.534%

    No Known Activations