Papers by Anirudh Joshi

2 papers
Reevaluating Argument Component Extraction in Low Resource Settings (D19-61)

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Challenge: Argument component extraction is a challenging and complex high-level semantic extraction task.
Approach: They propose to use character-level, GloVe, ELMo, and BERT encodings to compare arguments extracted using standard BiLSTM-CRF encoders.
Outcome: The proposed approaches perform better than baselines in higher-level semantic extraction tasks and suggest future improvements.
Dr. Summarize: Global Summarization of Medical Dialogue by Exploiting Local Structures. (2020.findings-emnlp)

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Challenge: Summarization of medical conversations addresses a very real need in medical practice: capturing the most important aspects of a medical encounter.
Approach: They propose a novel approach to medical conversation summarization that leverages the unique and independent local structures created when gathering a patient’s medical history.
Outcome: The proposed model captures most or all of the information in 80% of the medical conversations making it a realistic alternative to costly manual summarization by medical experts.

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