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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 E2E Recon
    9. 6-RES_SCEFR-AJT
    11. 2002
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    Explanations

    names of countries or cities followed by specific references such as 'will try and rough up France,' or specific events like 'World Cup.'

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    neuronpedia/gpt2-small__res_scefr-ajt/6-res_scefr-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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    No Comments

    Neuron Alignment
    Index
    Value
    % of L₁
    288
    +0.20
    0.7%
    128
    +0.19
    0.7%
    267
    +0.17
    0.6%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    606
    +0.20
    0.06
    128
    +0.19
    0.05
    67
    +0.17
    0.06
    Negative Logits
    EStream
    -1.28
    veyard
    -1.15
    ippi
    -1.10
    ibilities
    -1.10
    oute
    -1.02
     reperto
    -1.01
    iple
    -1.01
    »Ĵ
    -1.00
    WARE
    -0.98
    odox
    -0.98
    POSITIVE LOGITS
     Trade
    1.15
     Reincarn
    1.15
     Championships
    1.14
     Wide
    1.12
     Airways
    1.11
     Organisation
    1.11
     Order
    1.10
     Federation
    1.09
     Organization
    1.08
     Series
    1.06
    Activations Density 0.544%

    No Known Activations