Papers with QuASAR

2 papers
P-QuASAR: A Unified Probabilistic Framework for Holistic Patent Quality Assessment and Refinement (2026.findings-acl)

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Challenge: Existing methods for assessing patent quality rely on modular pipelines or generic detectors, resulting in fragmented decisions and limited integration across quality dimensions.
Approach: They propose a probabilistic framework that represents patent specifications as Quality Graphs.
Outcome: The proposed framework outperforms existing methods on 500 patents against seven baselines.
QuASAR: A Question-Driven Structure-Aware Approach for Table-to-Text Generation (2025.acl-long)

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Challenge: Existing methods for table-to-text generation fail to capture the structure of tabular data or rely on complex attention mechanisms, limiting their applicability.
Approach: They propose a question-driven self-supervised approach to enhance the model’s structural perception and representation capabilities by focusing on structure-related queries.
Outcome: The proposed model improves its model's structural perception and representation capabilities by guiding it to capture local and global table structures.

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