Papers by Pantea Haghighatkhah

2 papers
Story Trees: Representing Documents using Topological Persistence (2022.lrec-1)

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Challenge: Topological data analysis (TDA) focuses on the inherent shape of (spatial) data.
Approach: They propose to use topological data analysis to represent document structure as story trees . story trees are hierarchical representations created from semantic vector representations of sentences .
Outcome: The proposed methods can be used to extract summary summaries from news stories using story trees.
Better Hit the Nail on the Head than Beat around the Bush: Removing Protected Attributes with a Single Projection (2022.emnlp-main)

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Challenge: Existing methods to remove specific information from embeddings are based on multiple iterations, but multiple iters increase the risk of negative effects.
Approach: They propose two methods that find a single targeted projection: Mean Projection and Tukey Median Projection.
Outcome: The proposed method removes biases by removing information from embedding spaces . it is cleaner than the previous method because it removes separability based on the target .

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