Papers with deep-learning based NLP models

2 papers
Where to Attack: A Dynamic Locator Model for Backdoor Attack in Text Classifications (2022.coling-1)

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Challenge: BackDoor Attack (BDA) study aims to train a poisoned model with clean data and some trigger-embedded instances to perform normally on normal inputs.
Approach: They propose to train a poisoned model with clean and poisonest inputs . they propose to use triggers to predict those poisonets as target labels .
Outcome: The proposed model can predict P2P dynamically without human intervention.
Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness? (2020.acl-main)

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Challenge: Current approaches to interpretability evaluation focus on faithfulness criteria . current approaches focus on readability, plausibility and faithfulness .
Approach: They argue that current binary definition of faithfulness sets unrealistic standards . they argue that a more graded definition would be of greater practical utility .
Outcome: The proposed approach is based on three assumptions and lacks a graded definition of faithfulness.

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