PhD Candidate · Cornell University
Shaden Shaar
I'm a PhD candidate in Computer Science at Cornell University, advised by Prof. Claire Cardie. My thesis focuses on NLP tasks over long inputs — some of which involve long-form generation — most recently open-ended question-answering and summarization over full-length videos, which produced MovieRecapsQA (CVPR 2026). In parallel, I collaborate with NewYork-Presbyterian Hospital on clinical NLP for heart failure and heart transplant care.
Before Cornell, I was at the Qatar Computing Research Institute (QCRI, HBKU) working with Prof. Preslav Nakov on automated fact-checking, propaganda detection, and COVID-19 misinformation — including That Is a Known Lie (ACL 2020), which introduced the task of detecting previously fact-checked claims.
News
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MovieRecapsQA, our open-ended benchmark for question-answering over full-length movies, appeared at CVPR 2026.
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Our JHLT paper with NewYork-Presbyterian uses an LLM for thematic analysis of accepted heart-transplant exception requests.
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Wrapped up a summer as an Applied Scientist Intern at Zillow, building conversational real-estate agents with reinforcement learning.
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"Are Triggers Needed for Document-Level Event Extraction?" was published in TACL. Also finished an ML research engineering internship at Scale AI.
Research interests
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NLP over long inputs
Question-answering and summarization over full-length videos and other extended, multi-modal narratives — including the long-form generation some of these tasks demand, and the challenge of evaluating open-ended outputs no fixed reference can capture.
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Clinical NLP
Using LLMs to surface clinical decision patterns from unstructured medical narratives, with a focus on heart failure and heart transplant care.
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Automated fact-checking prior
Detecting, verifying, and justifying claim veracity across multi-modal, variable-length inputs.
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Propaganda detection prior
Identifying propaganda and persuasion techniques across multi-modal inputs in news articles, memes, and other media.
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COVID-19 misinformation prior
Analyzing misinformation, vaccine-related fake news, and the broader infodemic on social platforms during the COVID-19 pandemic.
Experience
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Applied Scientist Intern · Zillow Group
Remote, USA
- Built conversational assistive AI agents for Zillow's real-estate platform using reinforcement-learning methods.
- Designed reward-modeling and evaluation pipelines for grounded multi-turn property-search dialogue.
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Machine Learning Research Engineer Intern · ScaleAI, Inc.
New York City, NY, USA
- Built an Arabic-language AI assistant for the Qatari judicial department to aid judges reviewing active cases.
- Implemented dense and sparse retrieval over Arabic cassation and supreme-court rulings for relevant-precedent lookup.
- Designed Arabic case-summarization and event-extraction pipelines feeding the judge-facing platform.
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AI/ML Research Intern · Apple
Seattle, WA, USA
- Worked with Dr. Alex Churchill on zero-shot multi-turn conversation data generation.
- Built a model that generates conditioned multi-turn dialogue datasets for downstream training.
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Research Assistant · Qatar Computing Research Institute (QCRI), HBKU
Doha, Qatar
- Worked with Dr. Preslav Nakov and Prof. Giovanni Da San Martino on fact-checking and propaganda detection.
- Introduced the task of detecting previously fact-checked claims; methods adopted by leading fact-checking organizations.
- Built fact-checking and analysis pipelines for COVID-19 misinformation across social platforms.
- Co-organized shared tasks at CLEF–CheckThat! (2020, 2021) and SemEval–2021 Task 6 on persuasion in memes.
- Built and shipped Prta, a public propaganda-analysis demo (ACL 2020 Best Demo, Honorable Mention).
Selected publications
All 32 publications →A few representative papers. The full list is on the publications page and Google Scholar.
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Thematic Analysis of Accepted Exception Requests for Heart Transplant Candidates Using a Large Language ModelJ. Frye, Shaden Shaar, C. Cardie, E. DeFilippis, D. Estrin, G. Sayer, N. Uriel, et al.
Uses an LLM to perform thematic analysis of accepted exception requests for heart transplant candidates, surfacing the clinical rationales that drive decisions in a setting where manual review at scale is infeasible.
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MovieRecapsQA: A Multimodal Open-Ended Video Question-Answering BenchmarkShaden Shaar, B. Thymes, S. Chaixanien, C. Cardie, B. Hariharan
An open-ended video-QA benchmark built from movie recaps that stress-tests whether models can reason over long-form narrative, not just short clips. Paired with baselines that expose a large gap between human and model performance on grounded, cross-modal questions.
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Are Triggers Needed for Document-Level Event Extraction?Shaden Shaar, W. Chen, M. Chatterjee, B. Wang, W. Zhao, C. Cardie
Revisits a long-standing assumption in event extraction — that explicit trigger annotations are required — and shows that trigger-free formulations can match or exceed trigger-based pipelines at the document level.
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Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a DocumentShaden Shaar, N. Georgiev, F. Alam, G. Da San Martino, A. Mohamed, P. Nakov
Scales fact-checked-claim detection from isolated sentences to full documents, where each claim must be located and matched jointly. Introduces a document-level dataset and retrieval+ranking system tuned for real fact-checker workflows.
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Best Demo Award, Honorable Mention
Prta: A System to Support the Analysis of Propaganda Techniques in the NewsG. Da San Martino, Shaden Shaar, Y. Zhang, S. Yu, A. Barrón-Cedeño, P. Nakov
An end-to-end system for highlighting 18 propaganda techniques in news articles, paired with a public web interface. Recognized with an Honorable Mention for Best Demo at ACL 2020.
- That Is a Known Lie: Detecting Previously Fact-Checked Claims
Shaden Shaar, G. Da San Martino, N. Babulkov, P. Nakov
Formalizes "previously fact-checked claim detection" as a ranking task and releases the first dataset for it, showing that reusing existing fact-checks is a practical alternative to verifying every claim from scratch.
Education
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PhD in Computer Science
Cornell University · Ithaca, NY
Advised by Prof. Claire Cardie · Minor in Applied Mathematics · Graduating Jan 2027
University Fellowship (2021)
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MS in Computer Science
Cornell University · Ithaca, NY
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BS in Computer Science
Carnegie Mellon University · Doha, Qatar
Minor in Mathematics · University Honors
50% Academic Merit Scholarship (2015)
Contact
The best way to reach me is by email at sshaar31@gmail.com — whether about roles, collaborations, or anything related to the work. A printable CV is available as a PDF.