Search Results for author: Litton J Kurisinkel

Found 8 papers, 1 papers with code

Coherent and Concise Radiology Report Generation via Context Specific Image Representations and Orthogonal Sentence States

no code implementations NAACL 2021 Litton J Kurisinkel, Ai Ti Aw, Nancy F Chen

Neural models for text generation are often designed in an end-to-end fashion, typically with zero control over intermediate computations, limiting their practical usability in downstream applications.

Text Generation

Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes

no code implementations IJCNLP 2019 Litton J Kurisinkel, Nancy Chen

This task differs from other natural language generation tasks in the following ways: (1) The input is a set of identifiable entities (ICD codes) where the relations between individual entity are not explicitly specified.

Recipe Generation Text Generation

Attention-based Neural Text Segmentation

1 code implementation29 Aug 2018 Pinkesh Badjatiya, Litton J Kurisinkel, Manish Gupta, Vasudeva Varma

Text segmentation plays an important role in various Natural Language Processing (NLP) tasks like summarization, context understanding, document indexing and document noise removal.

Feature Engineering Sentence Embeddings +1

SSAS: Semantic Similarity for Abstractive Summarization

no code implementations IJCNLP 2017 Raghuram Vadapalli, Litton J Kurisinkel, Manish Gupta, Vasudeva Varma

Ideally a metric evaluating an abstract system summary should represent the extent to which the system-generated summary approximates the semantic inference conceived by the reader using a human-written reference summary.

Abstractive Text Summarization Natural Language Inference +2

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