Papers by Anup Das

1 papers
Robertha: Eigenspectrum Regularized Attention for Robust Natural Language Understanding (2026.acl-long)

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Challenge: Existing robustness methods sacrifice clean performance or fail to generalize to higher corruption levels.
Approach: They propose a mechanism that uses semantic patterns to pull corrupted embeddings toward correct representations by Eigenspectrum Regularization.
Outcome: The proposed mechanism outperforms robustness methods on 13 GLUE and SuperGLUE tasks while maintaining competitive clean performance.

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