---
title: "Tristan Naumann — all works — Elamur Research"
description: "All 43 works of Tristan Naumann in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/tristan-naumann/works/"
---
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# Tristan Naumann — all works

43 works · [← Tristan Naumann](https://md.research.elamur.ai/free/en/authors/tristan-naumann/)

1. [**Publicly Available Clinical BERT Embeddings arXiv:1904.03323**Emily Alsentzer, John R. Murphy, Willie Boag, et al.*2019 · 1,233 citations*](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/)
2. **[A whole-slide foundation model for digital pathology from real-world data ↗](https://doi.org/10.1038/s41586-024-07441-w) Nature · no summary yet**Hanwen Xu et al.*2024 · 904 citations*
3. **[LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day](https://md.research.elamur.ai/free/en/papers/li-2023-llava-med-training-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chunyuan Li, Cliff Wong, Sheng Zhang, et al.*2023 · 692 citations*
4. **[Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing ↗](https://doi.org/10.1007/978-3-031-20059-5_1) Lecture notes in computer science · no summary yet**Benedikt Boecking et al.*2022 · 312 citations*
5. **[A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs ↗](https://doi.org/10.1056/aioa2400640) NEJM AI · no summary yet**Sheng Zhang et al.*2024 · 280 citations*
6. **[Fine-tuning large neural language models for biomedical natural language processing ↗](https://doi.org/10.1016/j.patter.2023.100729) Patterns · no summary yet**Robert Tinn et al.*2021 · 198 citations*
7. **[A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data ↗](https://doi.org/10.1609/aaai.v29i1.9209) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Marzyeh Ghassemi et al.*2015 · 197 citations*
8. **[BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs ↗](https://arxiv.org/abs/2303.00915) arXiv (Cornell University) · no summary yet**Sheng Zhang et al.*2023 · 146 citations*
9. **[A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities ↗](https://doi.org/10.1038/s41592-024-02499-w) Nature Methods · no summary yet**Theodore Zhao et al.*2024 · 110 citations*
10. **[Multimodal AI generates virtual population for tumor microenvironment modeling ↗](https://doi.org/10.1016/j.cell.2025.11.016) Cell · no summary yet**Jeya Maria Jose Valanarasu et al.*2025 · 57 citations*
11. **[Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation ↗](https://doi.org/10.1038/s41467-025-58344-x) arXiv:2403.08002 · Nature Communications volume 16, Article number: 3108 (2025) · no summary yet**Juan Manuel Zambrano Chaves et al.*2024 · 57 citations*
12. [**Self-Verification Improves Few-Shot Clinical Information Extraction arXiv:2306.00024 · IMLH 2023**Zelalem Gero, Chandan Singh, Hao Cheng, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gero-2023-self-verification-improves-few-shot/)
13. **[Knowledge-Rich Self-Supervision for Biomedical Entity Linking ↗](https://aclanthology.org/2022.findings-emnlp.61/) Findings of the Association for Computational Linguistics: EMNLP 2022 · no summary yet**Sheng Zhang et al.*2022 · 49 citations*
14. **[Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology ↗](https://arxiv.org/abs/2308.02180) arXiv (Cornell University) · no summary yet**Cliff Wong et al.*2023 · 36 citations*
15. **[Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision ↗](https://doi.org/10.1016/j.patter.2023.100726) Patterns · no summary yet**Sam Preston et al.*2023 · 34 citations*
16. **[Biomedical Natural Language Processing in the Era of Large Language Models ↗](https://doi.org/10.1146/annurev-biodatasci-103123-095406) Annual Review of Biomedical Data Science · no summary yet**Naoto Usuyama et al.*2025 · 25 citations*
17. **[Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events ↗](https://arxiv.org/abs/2307.06439) arXiv (Cornell University) · no summary yet**Gu, Yu et al.*2023 · 22 citations*
18. **[Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning ↗](https://arxiv.org/abs/2502.19655) arXiv (Cornell University) · no summary yet**Sheng Zhang et al.*2025 · 21 citations*
19. **[DocLens: Multi-aspect Fine-grained Evaluation for Medical Text Generation ↗](https://aclanthology.org/2024.acl-long.39/) Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Yiqing Xie et al.*2024 · 18 citations*
20. **[Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature ↗](https://doi.org/10.1145/3447548.3469053) arXiv:2106.13375 · no summary yet**Yu Wang et al.*2021 · 17 citations*
21. **[Modular Self-Supervision for Document-Level Relation Extraction ↗](https://aclanthology.org/2021.emnlp-main.429/) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yet**Sheng Zhang et al.*2021 · 13 citations*
22. **[TRIALSCOPE — A Framework for Clinical Trial Simulation from Real-World Data ↗](https://doi.org/10.1056/aioa2400859) NEJM AI · no summary yet**Javier González Hernández et al.*2025 · 11 citations*
23. **[Continual Contrastive Finetuning Improves Low-Resource Relation Extraction ↗](https://aclanthology.org/2023.acl-long.739/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Wenxuan Zhou et al.*2023 · 9 citations*
24. **[Compositional Zero-Shot Domain Transfer with Text-to-Text Models ↗](https://aclanthology.org/2023.tacl-1.62/) Transactions of the Association for Computational Linguistics · no summary yet**Fangyu Liu et al.*2023 · 8 citations*
25. **[The Illusion of Readiness in Health AI ↗](https://arxiv.org/abs/2509.18234) arXiv (Cornell University) · no summary yet**Gu, Yu et al.*2025 · 7 citations*
26. **[BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once ↗](https://arxiv.org/abs/2405.12971) arXiv (Cornell University) · no summary yet**Theodore Zhao et al.*2024 · 7 citations*
27. **[Generative Medical Event Models Improve with Scale ↗](https://arxiv.org/abs/2508.12104) arXiv (Cornell University) · no summary yet**Shane Waxler et al.*2025 · 6 citations*
28. **[X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains ↗](https://arxiv.org/abs/2505.03981) arXiv (Cornell University) · no summary yet**Qianchu Liu et al.*2025 · 5 citations*
29. **[Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation ↗](https://arxiv.org/abs/1912.04370) arXiv:1912.04370 · no summary yet**Aparna Balagopalan et al.*2019 · 5 citations*
30. **[Evaluating the robustness and readiness of large frontier models in health AI applications ↗](https://doi.org/10.1038/s41591-026-04501-8) Nature Medicine · no summary yet**裕二 池谷 et al.*2026 · 4 citations*
31. **[Exploring Scaling Laws for EHR Foundation Models ↗](https://arxiv.org/abs/2505.22964) arXiv (Cornell University) · no summary yet**Sheng Zhang et al.*2025 · 4 citations*
32. **[Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries ↗](https://arxiv.org/abs/2403.01002) arXiv (Cornell University) · no summary yet**Zelalem Gero et al.*2024 · 4 citations*
33. **[TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models ↗](https://arxiv.org/abs/2311.01301) arXiv (Cornell University) · no summary yet**Javier González et al.*2023 · 4 citations*
34. **[Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision ↗](https://arxiv.org/abs/2203.10442) arXiv (Cornell University) · no summary yet**Sam Preston et al.*2022 · 4 citations*
35. **[Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale ↗](https://arxiv.org/abs/2502.00943) arXiv (Cornell University) · no summary yet**Cliff Wong et al.*2025 · 3 citations*
36. **[BiomedParse-V: Scaling Foundation Model for Universal Text-Guided Volumetric Biomedical Image Segmentation ↗](https://doi.org/10.1007/978-3-032-23496-4_7) Lecture notes in computer science · no summary yet**Theodore Zhao et al.*2026 · 2 citations*
37. **[Exploring the Future of AI in Clinical Collaboration: A Study on Tumor Board Case Preparation ↗](https://doi.org/10.1145/3772318.3790448) CHI Conference on Human Factors in Computing Systems · no summary yet**Jiachen Li et al.*2026 · 1 citation*
38. **[GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis ↗](https://arxiv.org/abs/2607.18218) arXiv:2607.18218 · no summary yet**Naoto Usuyama et al.*2026 · 1 citation*
39. **[Large Language Models are Approximate Survival Estimators ↗](https://arxiv.org/abs/2609.38181) arXiv (Cornell University) · no summary yet**Juan Manuel Zambrano Chaves et al.*2026*
40. **[HealthAgentBench: A Unified Benchmark Suite of Realistic Agentic Healthcare Environments for Challenging Frontier AI Agents ↗](https://arxiv.org/abs/2606.31179) arXiv (Cornell University) · no summary yet**Qianchu Liu et al.*2026*
41. **[Scaling medical imaging report generation with multimodal reinforcement learning ↗](https://arxiv.org/abs/2601.17151) arXiv (Cornell University) · no summary yet**Qianchu Liu et al.*2026*
42. **[Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models ↗](https://arxiv.org/abs/2609.12277) arXiv (Cornell University) · no summary yet**Yuxin Xiao et al.*2026*
43. **[Learning Sparse Visual Representations via Spatial-Semantic Factorization ↗](https://arxiv.org/abs/2602.01905) arXiv (Cornell University) · no summary yet**Theodore Zhengde Zhao et al.*2026*