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    2. Apollo Research · Taylor · Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
    3. GPT2-Small
    4. Residual Similar CE Local
    5. 6-RES_SCL-AJT
    6. 45554
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    concepts related to environmental issues and pollution, particularly focusing on pollution in various contexts such as water pollution and air pollution

    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
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    Neuron Alignment
    Index
    Value
    % of L₁
    447
    +0.23
    1.3%
    679
    +0.11
    0.6%
    288
    +0.10
    0.6%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    526
    +0.23
    -0.07
    288
    +0.11
    0.18
    119
    +0.10
    0.08
    Negative Logits
    llan
    -0.65
    laus
    -0.60
    inosaur
    -0.60
    ndra
    -0.59
    Bone
    -0.59
    pha
    -0.57
    tre
    -0.56
    orian
    -0.55
    donald
    -0.55
    antine
    -0.55
    POSITIVE LOGITS
     pollution
    0.77
     fumes
    0.67
     pollutants
    0.66
     pollut
    0.64
     emissions
    0.64
     polluted
    0.62
    ution
    0.62
     contamin
    0.62
     streams
    0.60
     spew
    0.60
    Activations Density 7.188%

    No Known Activations