Papers by Van-Cuong Pham

3 papers
Householder Pseudo-Rotation: A Novel Approach to Activation Editing in LLMs with Direction-Magnitude Perspective (2024.emnlp-main)

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Challenge: Existing methods to edit LLMs' activations are limited by their magnitude and direction consistency.
Approach: They propose a method that edits activations to alter their magnitudes and directions to preserve activation norms.
Outcome: The proposed method preserves activation norm and improves safety benchmarks.
Lifelong Event Detection via Optimal Transport (2024.emnlp-main)

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Challenge: Continual event detection (CED) is a challenging task due to catastrophic forgetting, where learning new tasks hampers performance on previous ones.
Approach: They propose a method that leverages optimal transport principles to align the optimization of a classification module with the intrinsic nature of each class, as defined by their pre-trained language modeling.
Outcome: The proposed method outperforms state-of-the-art methods on MAVEN and ACE datasets and is a pioneering solution in continual event detection.
Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI (2026.acl-long)

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Challenge: Existing methods struggle with content-style entanglement, leading to poor generalization across domains.
Approach: They propose an explanation-by-design framework that explicitly disentangles style from content through architectural separation-by design.
Outcome: The proposed framework disentangles style from content through architectural separation-by-design.

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