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Marzyeh Ghassemi

Marzyeh Ghassemi has 2 papers in our library, in 2020–2026, most of them on Language models & pretraining; often with Kyunghyun Cho, Nathan Ng, Shujian Zhang.

2 papers in our library · 2020–2026

OpenAlex · ORCID · Wikidata · h-index 58 · 335 works · 21,104 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 99 times in our library · 9 more in our library without a page yet · ⭐ Paper Stars ranking: #6027

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Massachusetts Institute of TechnologyCambridge · United States2012–2026 · 176 papersEducation until 2017 · PhD, EECSEmploymentcurrent🏢MicrosoftRedmond · United States2019–2026 · 3 paperscurrent🏢Microsoft ResearchCambridge · United Kingdom2026 · 1 papercurrent🔬Vector InstituteToronto · Canada2018–2025 · 82 papersEmployment🎓University of TorontoToronto · Canada2018–2024 · 74 papersEmployment🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2014–2025 · 20 papers🔬Canadian Institute for Advanced ResearchToronto · Canada2020–2025 · 16 papers🏥Unity Health TorontoToronto2021–2022 · 6 papers🏥St. Michael's HospitalToronto · Canada2021–2022 · 4 papers🎓University of AlbertaEdmonton · Canada2021 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 35 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20261 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness (2020 · 161 citations)
    Classifiers and sequence models trained on one domain often perform poorly on out-of-domain (OOD) inputs. For images, simple transformations like rotation keep new examples realistic, but no comparable meaning-preserving operations exist for text. The authors propose SSMBA, a task-agnostic augmentation scheme based…
  2. SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe (2026 · 3 citations)
    Instruction tuning usually trains LLMs with plain next-token prediction (NTP). Most efforts to improve it focus on building cleaner SFT datasets, which often means filtering with proprietary LLMs or paying human annotators. SFTMix improves the training recipe itself and works on uncurated data.

All works

11 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetMarzyeh Ghassemi et al.2015 · 197 citations
  2. SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain RobustnessConference on Empirical Methods in Natural Language Processing (EMNLP)Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi2020 · 161 citations
  3. Vision-Language Models Do Not Understand Negation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetKumail Alhamoud et al.2025 · 36 citations
  4. Predicting Out-of-Domain Generalization with Neighborhood Invariance ↗arXiv (Cornell University) · no summary yetNg, Nathan et al.2022 · 5 citations
  5. Towards Characterizing the High-dimensional Bias of Kernel-based Particle Inference Algorithms ↗no summary yetJimmy Lei Ba et al.2019 · 5 citations
  6. Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation ↗arXiv:1912.04370 · no summary yetAparna Balagopalan et al.2019 · 5 citations
  7. Redefining druggable targets with artificial intelligence ↗Nature Biotechnology · no summary yetKaren Akinsanya et al.2025 · 4 citations
  8. SFTMix: Elevating Language Model Instruction Tuning with Mixup RecipeAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxin Xiao, Shujian Zhang, Marzyeh Ghassemi, et al.2026 · 3 citations
  9. Improving Black-box Robustness with In-Context Rewriting ↗arXiv (Cornell University) · no summary yetKyle O'Brien et al.2024 · 3 citations
  10. Hedging and Non-Affirmation: Quantifying LLM Alignment on Questions of Human Rights ↗arXiv:2502.19463 · no summary yetRafiya Javed et al.2025 · 2 citations
  11. Protecting patient privacy in clinical foundation models: Technical and legal perspectives ↗arXiv:2608.07705 · no summary yetSana Tonekaboni et al.2026

 Co-authors here

4 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 99 times (of the 149,439 papers whose bibliographies we read); 11 citing papers with a page here →.

Updated

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