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Complex Mathematical Symbol Definition Structures: A Dataset and Model for Coordination Resolution in Definition Extraction
Anna Martin-Boyle, Andrew Head, Kyle Lo, Risham Sidhu, Marti A. Hearst, Dongyeop KangarXiv • 2023 Mathematical symbol definition extraction is important for improving scholarly reading interfaces and scholarly information extraction (IE). However, the task poses several challenges: math symbols are difficult to process as they are not composed of natural…Decomposing Complex Queries for Tip-of-the-tongue Retrieval
Kevin Lin, Kyle Lo, Joseph E. Gonzalez, Dan KleinarXiv • 2023 When re-finding items, users who forget or are uncertain about identifying details often rely on creative strategies for expressing their information needs -- complex queries that describe content elements (e.g., book characters or events), information beyond…Learning to Generate Novel Scientific Directions with Contextualized Literature-based Discovery
Qingyun Wang, Doug Downey, Heng Ji, Tom HopearXiv.org • 2023 Literature-Based Discovery (LBD) aims to discover new scientific knowledge by mining papers and generating hypotheses. Standard LBD is limited to predicting pairwise relations between discrete concepts (e.g., drug-disease links), and ignores critical contexts…TESS: Text-to-Text Self-Conditioned Simplex Diffusion
Rabeeh Karimi Mahabadi, Jaesung Tae, Hamish Ivison, J. Henderson, Iz Beltagy, Matthew E. Peters, Arman CohanarXiv • 2023 Diffusion models have emerged as a powerful paradigm for generation, obtaining strong performance in various domains with continuous-valued inputs. Despite the promises of fully non-autoregressive text generation, applying diffusion models to natural language…Embedding Recycling for Language Models
Jon Saad-Falcon, Amanpreet Singh, Luca Soldaini, Mike D'Arcy, Arman Cohan, Doug DowneyFindings of EACL • 2023 Training and inference with large neural models is expensive. However, for many application domains, while new tasks and models arise frequently, the underlying doc-uments being modeled remain mostly un-changed. We study how to decrease computational cost in…LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization
Kalpesh Krishna, Erin Bransom, Bailey Kuehl, Mohit Iyyer, Pradeep Dasigi, Arman Cohan, Kyle LoEACL • 2023 While human evaluation remains best practice for accurately judging the faithfulness of automatically-generated summaries, few solutions exist to address the increased difficulty and workload when evaluating long-form summaries. Through a survey of 162 papers…S2abEL: A Dataset for Entity Linking from Scientific Tables
Yuze Lou, Bailey Kuehl, Erin Bransom, Sergey Feldman, Aakanksha Naik, Doug DowneyEMNLP • 2023 Entity linking (EL) is the task of linking a textual mention to its corresponding entry in a knowledge base, and is critical for many knowledge-intensive NLP applications. When applied to tables in scientific papers, EL is a step toward large-scale scientific…CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context
Joseph Chee Chang, Amy X. Zhang, Jonathan Bragg, Andrew Head, Kyle Lo, Doug Downey, Daniel S. WeldCHI • 2023 When reading a scholarly article, inline citations help researchers contextualize the current article and discover relevant prior work. However, it can be challenging to prioritize and make sense of the hundreds of citations encountered during literature…ComLittee: Literature Discovery with Personal Elected Author Committees
Hyeonsu B Kang, Nouran Soliman, Matt Latzke, Joseph Chee Chang, Jonathan BraggCHI • 2023 In order to help scholars understand and follow a research topic, significant research has been devoted to creating systems that help scholars discover relevant papers and authors. Recent approaches have shown the usefulness of highlighting relevant authors…Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections
Srishti Palani, Aakanksha Naik, Doug Downey, Amy X. Zhang, Jonathan Bragg, Joseph Chee ChangCHI • 2023 Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly challenging. Meanwhile, authors summarize prior research in papers…