Fahim Dalvi, Nadir Durrani, Hassan Sajjad
We lifted 1 functions out of this paper's own repositories and ran 1 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| fdalvi/NeuroX | — | 1 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| LinearProbe | Ran | fdalvi/NeuroX/neurox/interpretation/linear_probe.py code served (permissive licence) · get_code("d37d66b1839784d8") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Neuron analysis provides insights into how knowledge is structured in representations and discovers the role of neurons in the network. In addition to developing an understanding of our models, neuron analysis enables various applications such as debiasing, domain adaptation and architectural search. We present NeuroX, a comprehensive open-source toolkit to conduct neuron analysis of natural language processing models. It implements various interpretation methods under a unified API, and provides a framework for data processing and evaluation, thus making it easier for researchers and practitioners to perform neuron analysis. The Python toolkit is available at https://www.github. com/fdalvi/NeuroX.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2305.17073")
get_code_for_paper("2305.17073")
have("2305.17073")
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