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    3. Apollo Research · Taylor · Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
    5. GPT2-Small
    7. Residual Similar CE Local
    9. 6-RES_SCL-AJT
    11. 32768
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    information related to aviation and aerospace engineering, including terms like "aviation sector," "automotive industry," "aircraft," "aviation safety," "aerospace manufacturing," and "aerospace engineering."

    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
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    Neuron Alignment
    Index
    Value
    % of L₁
    288
    +0.20
    0.9%
    447
    +0.18
    0.8%
    57
    +0.10
    0.5%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    447
    +0.20
    0.26
    138
    +0.18
    0.24
    64
    +0.10
    -0.21
    Negative Logits
    ifier
    -0.96
    ividual
    -0.91
    ifiers
    -0.90
    abee
    -0.85
    gs
    -0.84
    steen
    -0.83
    gling
    -0.81
    hift
    -0.80
    bah
    -0.78
    imus
    -0.77
    POSITIVE LOGITS
     industry
    1.15
     establishments
    0.97
     sector
    0.96
     engineering
    0.94
     industries
    0.91
     conglomer
    0.90
     fraternity
    0.90
     infrastructure
    0.88
     conglomerate
    0.87
     professionals
    0.87
    Activations Density 10.567%

    No Known Activations