Papers by John Giorgi

3 papers
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval (2023.findings-emnlp)

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Challenge: Multi-document summarization (MDS) assumes a set of topic-related documents is provided as input.
Approach: They formalize the task and bootstrap it using existing datasets, retrievers and summarizers.
Outcome: The proposed method reduces the sensitivity of summarizers to imperfect retrieval, but is highly sensitive to other errors.
TOPICAL: TOPIC Pages AutomagicaLly (2024.naacl-demo)

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Challenge: Topic pages aggregate useful information about an entity or concept into a single concise article.
Approach: They propose a web app that generates topic pages for biomedical entities on demand . they use large language models and retrieval-augmented generation to generate high-quality topics .
Outcome: The proposed method is based on a human evaluation of 150 biomedical topics . it uses large language models and retrieval-augmented generation (RAG)
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations (2021.acl-long)

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Challenge: Sentence embeddings are an important component of many natural language processing systems.
Approach: They propose a self-supervised objective for learning universal sentence embeddings that does not require labelled training data.
Outcome: The proposed approach closes the performance gap between unsupervised and supervised pretraining for universal sentence encoders.

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