Papers by Sean Papay
Which Demographics do LLMs Default to During Annotation? (2025.acl-long)
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Johannes Schäfer, Aidan Combs, Christopher Bagdon, Jiahui Li, Nadine Probol, Lynn Greschner, Sean Papay, Yarik Menchaca Resendiz, Aswathy Velutharambath, Amelie Wuehrl, Sabine Weber, Roman Klinger
| Challenge: | Demographics and cultural background of annotators influence the labels they assign in text annotation. |
| Approach: | They examine the attributes of human annotators LLMs inherently mimic and compare them to demographic-conditioned prompts and placebo-conditioned ones. |
| Outcome: | The proposed model incorporates demographics and cultural background into the output of the large language models (LLMs) to evaluate which attributes of human annotators LLMs inherently mimic. |
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction (D18-2)
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| Challenge: | Comparability of models across tasks is lacking in most machine learning systems for natural language processing. |
| Approach: | They propose a framework for declarative specification and compilation of template-based information extraction that uses a generic specification language for the task and for data annotations in terms of spans and frames. |
| Outcome: | The proposed framework enables representation of a large variety of natural language processing tasks. |
RiQuA: A Corpus of Rich Quotation Annotation for English Literary Text (2020.lrec-1)
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| Challenge: | In literature, spoken interactions between characters are of central importance to the narrative. |
| Approach: | They propose to annotate quotations, including their interpersonal structure, for English literary text. |
| Outcome: | The proposed dataset provides a rich view of dialogue structures not available from other available corpora. |
Medical Summarization in Practice: Design, Deployment, and Analysis of a Clinical Summarization System for a German Hospital (2026.eacl-industry)
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| Challenge: | a large number of EHRs are created for a patient, which must be summarized into a discharge summary. |
| Approach: | They propose to integrate a clinical summarization system into a live german hospital workflow to help with the generation of discharge summaries. |
| Outcome: | The proposed system can be used in a live german hospital to help with discharge summaries. |
Dissecting Span Identification Tasks with Performance Prediction (2020.emnlp-main)
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| Challenge: | Span identification tasks are a staple of applied NLP, but there is little insight on how their properties influence their difficulty. |
| Approach: | They propose to build a model to predict span ID performance for unseen span ID tasks that can support architecture choices. |
| Outcome: | The proposed model predicts span ID tasks for unseen span ID task in English, and the meta model predictable span ID performance. |