Papers by Abdul Khan

1 papers
Analyzing Encoded Concepts in Transformer Language Models (2022.naacl-main)

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Challenge: a new framework to analyze how latent concepts are encoded in representations learned in pre-trained lan-guage models is proposed . conceptX uses clustering to discover the encoded concepts and align them with a large set of human-defined concepts.
Approach: They propose a framework to analyze how latent concepts are encoded in representations learned within pre-trained lan-guage models.
Outcome: The proposed framework explains encoded concepts by aligning with human-defined concepts.

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