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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. 13356
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    Explanations

    phrases related to the melting or melting point of substances, especially in the contexts of ice, rock, and potentially other materials

    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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    Neuron Alignment
    Index
    Value
    % of L₁
    288
    +0.27
    1.1%
    101
    +0.17
    0.7%
    14
    +0.12
    0.5%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    53
    +0.27
    0.07
    650
    +0.17
    0.07
    326
    +0.12
    0.07
    Negative Logits
    =-=-=-=-=-=-=-=-
    -0.84
    RR
    -0.78
    udo
    -0.76
    ODUCT
    -0.74
    Guard
    -0.73
    issue
    -0.72
    alez
    -0.71
    unal
    -0.70
     Ascend
    -0.69
    ours
    -0.69
    POSITIVE LOGITS
    downs
    1.29
     melt
    1.01
     butter
    0.95
     melting
    0.94
     melted
    0.93
    down
    0.89
     melts
    0.86
     iceberg
    0.85
     lettuce
    0.82
    ting
    0.82
    Activations Density 0.784%

    No Known Activations