Papers by Adam Lelkes
SDOH-NLI: a Dataset for Inferring Social Determinants of Health from Clinical Notes (2023.findings-emnlp)
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| Challenge: | Social and behavioral determinants of health (SDOH) play a significant role in shaping health outcomes, and extracting these determinant from clinical notes is a first step to help healthcare providers systematically identify opportunities to provide appropriate care and address disparities. |
| Approach: | They propose a dataset that extracts social and behavioral determinants from clinical notes and uses them to form a natural language inference task. |
| Outcome: | The proposed dataset is based on publicly available notes and is more challenging than standard NLI benchmarks. |
How Does Generative Retrieval Scale to Millions of Passages? (2023.emnlp-main)
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Ronak Pradeep, Kai Hui, Jai Gupta, Adam Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, Vinh Tran
| Challenge: | generative retrieval is a new paradigm for information retrieval, enabling a sequence-to-sequence model with a single Transformer . generative encoders have been used on small corpora, but only on large ones . |
| Approach: | They propose to encode an entire document corpus within a single Transformer . they find generative retrieval is competitive with state-of-the-art dual encoders on small corpora . |
| Outcome: | The proposed approach is competitive with state-of-the-art dual encoders on small corpora, the study finds . the proposed approach only evaluates on document corporales on the order of 100K in size . |
SEMQA: Semi-Extractive Multi-Source Question Answering (2024.naacl-long)
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| Challenge: | Recent proposed long-form question answering systems have shown promising capabilities, but attributing and verifying their generated abstractive answers can be difficult. |
| Approach: | They propose a task that summarises multiple sources in a semi-extractive fashion . they create a dataset with human-written semi-extractive answers to natural and generated questions . |
| Outcome: | The proposed task summarizes multiple sources in a semi-extractive fashion and produces fine in-line attributions by-design that are easy to verify, interpret, and evaluate. |
AgreeSum: Agreement-Oriented Multi-Document Summarization (2021.findings-acl)
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| Challenge: | Existing studies on agreement-oriented multidocument summarization have focused on clusters of articles . a recent study focused on the use of a pretraining framework to summarize articles based on the "union" of the articles. |
| Approach: | They propose to use agreement-oriented multidocument summarization to provide agreement-orientated summaries that represent information common to all articles. |
| Outcome: | The proposed task is called agreement-oriented multidocument summarization . the authors apply the pretrained model PEGASUS onto the task . |