Papers by Manali Sharma

3 papers
Patentformer: A Novel Method to Automate the Generation of Patent Applications (2024.emnlp-industry)

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Challenge: Patentformer is a novel method for generating patent specification by fine-tuning the generative models with diverse sources of information, e.g., patent claims, drawing text, and brief descriptions of the drawings.
Approach: They propose a method for generating patent specification by fine-tuning generative models with diverse sources of information, e.g., patent claims, drawing text, and brief descriptions of the drawings.
Outcome: The proposed method generates patent specification in legal writing style and human-like quality may be better than the actual specification.
Ranking-Constrained Learning with Rationales for Text Classification (2022.findings-acl)

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Challenge: Existing approaches to text classification use labels and rationales as ranking constraints.
Approach: They propose a ranking-constrained loss function that combines cross-entropy loss with ranking losses as rationale constraints to speed up deep learning models with limited training data.
Outcome: The proposed approach outperforms baselines on three human-annotated datasets and shows that it is more efficient than existing approaches.
PatentVision: A multimodal method for drafting patent applications (2026.eacl-industry)

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Challenge: PatentVision integrates textual and visual inputs to generate patent specifications . existing systems fail to capture the nuanced interplay between textual, visual components .
Approach: They propose a multimodal framework that integrates textual and visual inputs to generate patent specifications.
Outcome: The proposed framework surpasses text-only methods in patent writing, the authors show . it integrates visual data to better represent intricate design features and functional connections .

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