Search Results for author: Jonathan Bragg

Found 13 papers, 6 papers with code

FLEX: Unifying Evaluation for Few-Shot NLP

2 code implementations NeurIPS 2021 Jonathan Bragg, Arman Cohan, Kyle Lo, Iz Beltagy

Few-shot NLP research is highly active, yet conducted in disjoint research threads with evaluation suites that lack challenging-yet-realistic testing setups and fail to employ careful experimental design.

Few-Shot Learning Language Modelling

ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews

1 code implementation21 Jun 2023 Mike D'Arcy, Alexis Ross, Erin Bransom, Bailey Kuehl, Jonathan Bragg, Tom Hope, Doug Downey

Revising scientific papers based on peer feedback is a challenging task that requires not only deep scientific knowledge and reasoning, but also the ability to recognize the implicit requests in high-level feedback and to choose the best of many possible ways to update the manuscript in response.

Paper Plain: Making Medical Research Papers Approachable to Healthcare Consumers with Natural Language Processing

1 code implementation28 Feb 2022 Tal August, Lucy Lu Wang, Jonathan Bragg, Marti A. Hearst, Andrew Head, Kyle Lo

When seeking information not covered in patient-friendly documents, like medical pamphlets, healthcare consumers may turn to the research literature.

RCT Rejection Sampling for Causal Estimation Evaluation

1 code implementation27 Jul 2023 Katherine A. Keith, Sergey Feldman, David Jurgens, Jonathan Bragg, Rohit Bhattacharya

We contribute a new sampling algorithm, which we call RCT rejection sampling, and provide theoretical guarantees that causal identification holds in the observational data to allow for valid comparisons to the ground-truth RCT.

Causal Identification

From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks

no code implementations21 Apr 2022 Hyeonsu B. Kang, Rafal Kocielnik, Andrew Head, Jiangjiang Yang, Matt Latzke, Aniket Kittur, Daniel S. Weld, Doug Downey, Jonathan Bragg

To improve the discovery experience we introduce multiple new methods for \em augmenting recommendations with textual relevance messages that highlight knowledge-graph connections between recommended papers and a user's publication and interaction history.

FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs

no code implementations16 Aug 2022 Harmanpreet Kaur, Doug Downey, Amanpreet Singh, Evie Yu-Yen Cheng, Daniel S. Weld, Jonathan Bragg

We implement our technique in a novel system, FeedLens, which is built over Semantic Scholar, a production system for navigating the scientific literature KG.

Knowledge Graphs

Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections

no code implementations13 Feb 2023 Srishti Palani, Aakanksha Naik, Doug Downey, Amy X. Zhang, Jonathan Bragg, Joseph Chee Chang

Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers.

Descriptive Navigate +1

Beyond Summarization: Designing AI Support for Real-World Expository Writing Tasks

no code implementations5 Apr 2023 Zejiang Shen, Tal August, Pao Siangliulue, Kyle Lo, Jonathan Bragg, Jeff Hammerbacher, Doug Downey, Joseph Chee Chang, David Sontag

In this position paper, we argue that developing AI supports for expository writing has unique and exciting research challenges and can lead to high real-world impacts.

PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers

no code implementations5 Mar 2024 Yoonjoo Lee, Hyeonsu B. Kang, Matt Latzke, Juho Kim, Jonathan Bragg, Joseph Chee Chang, Pao Siangliulue

With the rapid growth of scholarly archives, researchers subscribe to "paper alert" systems that periodically provide them with recommendations of recently published papers that are similar to previously collected papers.

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