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He and colleagues: DeBERTa disentangled attention

Contribution grade

Language-model architecture · Human-designed AI research method or resource

Reference score18,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Separated token content and position representations in attention and used an enhanced mask decoder, reporting improvements over BERT/RoBERTa baselines.

Scientific scope

Separated token content and position representations in attention and used an enhanced mask decoder, reporting improvements over BERT/RoBERTa baselines. Scope limitation: The 2020 preprint was published at ICLR 2021; benchmark gains depend on the paper's training and evaluation choices.

Evidence

The retained primary-source abstract, bibliographic record and stated review scope support this provisional assessment. No independent experimental replication by WRS is claimed. The 2020 preprint was published at ICLR 2021; benchmark gains depend on the paper's training and evaluation choices.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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