Papers with PASs

    2 papers
    Distance-Free Modeling of Multi-Predicate Interactions in End-to-End Japanese Predicate-Argument Structure Analysis (C18-1)

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    Challenge: Existing models for analyzing PASs in Japanese are lacking in identifying elliptical arguments.
    Approach: They propose to extend the input and last layers of a bidirectional recurrent neural network model to capture the potential interactions among multiple PASs.
    Outcome: The proposed models improve prediction accuracy on a benchmark corpus and achieve state-of-the-art on standardized corpus.
    PASs-MoE: Mitigating Misaligned Co-drift among Router and Experts via Pathway Activation Subspaces for Continual Learning (2026.acl-long)

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    Challenge: Existing LoRA-based Mixture-of-Experts (MoE) methods often jointly update the router and experts in an indiscriminate way, causing the router’s preferences to co-drift with experts’ adaptation pathways and exacerbate forgetting.
    Approach: They propose a LoRA-induced subspace that reflects which low-rank pathway directions an input activates in each expert, providing a capability-aligned coordinate system for routing and preservation.
    Outcome: The proposed method outperforms conventional continual learning baselines and MoE–LoRA variants in accuracy and resistance to forgetting, without increasing model parameters.

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