Papers by Ramya Akula

1 papers
Sentence Pair Embeddings Based Evaluation Metric for Abstractive and Extractive Summarization (2022.lrec-1)

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Challenge: Existing evaluation metrics, such as ROUGE and BLEU, rely on exact word matching and fail to capture semantic similarity.
Approach: They propose to use contextualized word or sentence embeddings to capture semantic similarity between sentences to evaluate text summarization methods.
Outcome: The proposed evaluation metric shows that it performs faster than the current state-of-the-art on the SummEval dataset.

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