Papers with independent components

3 papers
What does the sea say to the shore? A BERT based DST style approach for speaker to dialogue attribution in novels (2022.acl-long)

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Challenge: Existing systems can perform the first two tasks accurately, but attributing characters to direct speech is a challenging problem due to the narrator’s lack of explicit character mentions and the frequent use of nominal and pronominal coreference when such explicit mentions are made.
Approach: They propose a pipeline to extract characters and link them to their direct-speech utterances by using a novel's list of characters and a list of attributing them to the speaking characters.
Outcome: The proposed pipeline improves state-of-the-art models by 50% in F1-score compared with existing models .
Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test (2024.lrec-main)

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Challenge: Independent Component Analysis (ICA) is an algorithm for finding separate sources in a mixed signal.
Approach: They propose to use ICA to analyze word embeddings to quantify interpretability . they propose to automate word intruder test to quantify the components .
Outcome: The proposed algorithm can be used to find semantic features of words . it can be combined to find words that have features associated with the components .
Towards More Accurate Uncertainty Estimation In Text Classification (2020.emnlp-main)

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Challenge: Existing models of uncertainty score depend on winning score, which is the maximum probability in a semantic vector.
Approach: They propose to generate accurate uncertainty score by improving the confidence of winning scores by reducing the effect of overconfidence of winning score and considering the impact of different categories simultaneously.
Outcome: The proposed model reduces the effect of overconfidence of winning score and considers impact of different categories of uncertainty simultaneously.

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