Russ Biagio Altman
Russ Biagio Altman has 2 papers in our library, in 2021–2024, most of them on Language models & pretraining; often with Antoine Bosselut, Denny Zhou, Di Yin.
OpenAlex · ORCID · Wikidata · h-index 106 · 825 works · 53,347 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 1,003 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #1067
Affiliations
Fields, topics and concepts
📚 Shelves 10The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 1 workArts and Humanities · 1 workComputer Science · 1 workLanguage and Linguistics · 1 workSafety Research · 1 workSocial Sciences · 1 workBiochemistry, Genetics and Molecular Biology · 1 workHealth Informatics · 1 workMedicine · 1 workMolecular Biology · 1 work
🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works
💡 Concepts 2Key ideas and methods explained on our concept pages.Artificial intelligence · 1 workLarge language models · 1 work
Works by year
2020s
Papers
- On the Opportunities and Risks of Foundation Models (2021 · 3,160 citations)
This Stanford CRFM report surveys a new way of building AI. Large models are pretrained on broad data, usually through self-supervision at scale, and then adapted to many downstream tasks. The authors name these "foundation models" (examples: BERT, GPT-3, CLIP, DALL-E). The report does not propose a dataset or… - CRISPR-GPT for Agentic Automation of Gene-editing Experiments (2024 · 163 citations)
General-purpose LLMs such as ChatGPT-4 often perform poorly when asked to plan CRISPR experiments. They can produce guide RNA sequences that match no real genomic location, omit practical details like reagents, off-target checks and protocols, or bury useful advice in irrelevant text. The authors present CRISPR-GPT…
All works
- On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
- CRISPR-GPT for Agentic Automation of Gene-editing ExperimentsarXiv:2404.18021Yuanhao Qu, Kaixuan Huang, Ming Yin, et al.2024 · 163 citations
- Leveraging the Cell Ontology to classify unseen cell types ↗Nature Communications · no summary yetSheng Wang et al.2021 · 65 citations
- Multilingual translation for zero-shot biomedical classification using BioTranslator ↗Nature Communications · no summary yetHanwen Xu et al.2023 · 31 citations
- Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetDaniel Sosa et al.2023 · 5 citations
- Drugs and where to find them : multi-scale artificial intelligence methods for identifying ligand-binding pockets and opioid-related social media posts ↗Stanford Digital Repository · no summary yetKristy A. Carpenter et al.2026
- AutoScreen: AI Co-Scientist System for Target Discovery in Functional Genomics ↗bioRxiv (Cold Spring Harbor Laboratory) · no summary yetYuanhao Qu et al.2026
- Inducing Novel Gene-Drug Interactions from the Biomedical Literature ↗no summary yetSepandar D. Kamvar et al.2002
Co-authors here
- Antoine Bosselut
- Denny Zhou
- Di Yin
- Drew A. Hudson
- Emma Brunskill
- Kaixuan Huang
- Michael S. Bernstein
- Ming Yin
- Rishi Bommasani
- Simran Arora
- Sydney von Arx
Venues
- Nature Communications ×2
- Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Stanford Digital Repository
- bioRxiv (Cold Spring Harbor Laboratory)
Cited by
Updated
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