--- title: "Albert Gu — author profile and papers — Elamur Research" description: "Albert Gu, Carnegie Mellon University: 2 papers on Elamur Research (2023–2024), h-index 20 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/albert-gu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/albert-gu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Albert Gu # Albert Gu Albert Gu has 2 papers in our library, in 2023–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Antonio Orvieto](https://md.research.elamur.ai/free/en/authors/antonio-orvieto/), [Brandon Norick](https://md.research.elamur.ai/free/en/authors/brandon-norick/), [Caglar Gulcehre](https://md.research.elamur.ai/free/en/authors/caglar-gulcehre/). 2 papers in our library · 2023–2024 [OpenAlex](https://openalex.org/A5025386668) · [**h-index 20**](https://openalex.org/authors/A5025386668) · [57 works](https://openalex.org/works?filter=author.id:A5025386668) · [2,951 citations](https://openalex.org/works?filter=author.id:A5025386668&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/albert-gu/#papers) · [🔗 Cited 1,191 times in our library](https://md.research.elamur.ai/free/en/authors/albert-gu/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6636](https://md.research.elamur.ai/free/en/paper-stars/page/67/#star-6636) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Albert+Gu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Albert+Gu) · [dblp](https://dblp.org/search?q=Albert+Gu) · [ACL Anthology](https://aclanthology.org/search/?q=Albert+Gu) ## Affiliations [🎓**Carnegie Mellon University** Pittsburgh · United States 2013–2026 · 16 papers*current*](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Stanford University** Stanford · United States 2018–2023 · 23 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**University at Buffalo, State University of New York** Buffalo · United States 2018–2021 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-at-buffalo-state-university-of-new-york/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/albert-gu/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/albert-gu/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Resurrecting Recurrent Neural Networks for Long Sequences](https://md.research.elamur.ai/free/en/papers/orvieto-2023-resurrecting-recurrent-neural-networks-long/)** *(2023 · 118 citations)* Classic RNNs are cheap at inference on long inputs, but they train slowly and suffer from vanishing or exploding gradients. 2. **[An Empirical Study of Mamba-based Language Models](https://md.research.elamur.ai/free/en/papers/waleffe-2024-empirical-study-mamba-based-language/)** *(2024 · 67 citations)* Selective state-space models (SSMs) such as Mamba could make inference cheaper than in Transformers. They avoid attention's quadratic cost and the ever-growing key-value cache. However, earlier comparisons with identical training data covered only small models. This NVIDIA-led report addresses that gap. It trains… ## All works 7 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. **[Mamba: Linear-Time Sequence Modeling with Selective State Spaces ↗](https://arxiv.org/abs/2312.00752) arXiv:2312.00752 · no summary yet**Albert Gu, Tri Dao*2023 · 1,726 citations* 2. **[Efficiently Modeling Long Sequences with Structured State Spaces ↗](https://arxiv.org/abs/2111.00396) arXiv:2111.00396 · no summary yet**Albert Gu, Karan Goel, Christopher Ré*2021 · 791 citations* 3. **[HiPPO: Recurrent Memory with Optimal Polynomial Projections ↗](https://arxiv.org/abs/2008.07669) arXiv:2008.07669 · no summary yet**Albert Gu et al.*2020 · 205 citations* 4. [**Resurrecting Recurrent Neural Networks for Long Sequences arXiv:2303.06349**Antonio Orvieto, Samuel L Smith, Albert Gu, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/orvieto-2023-resurrecting-recurrent-neural-networks-long/) 5. [**An Empirical Study of Mamba-based Language Models arXiv:2406.07887**Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/waleffe-2024-empirical-study-mamba-based-language/) 6. **[Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models ↗](https://arxiv.org/abs/2408.10189) arXiv:2408.10189 · no summary yet**Aviv Bick et al.*2024 · 29 citations* 7. **[Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models ↗](https://arxiv.org/abs/2512.02636) arXiv (Cornell University) · no summary yet**Ai, Xinyue et al.*2025 · 1 citation* ## Co-authors here 9 co-authors with a page, the most papers together first. - [Antonio Orvieto](https://md.research.elamur.ai/free/en/authors/antonio-orvieto/) - [Brandon Norick](https://md.research.elamur.ai/free/en/authors/brandon-norick/) - [Caglar Gulcehre](https://md.research.elamur.ai/free/en/authors/caglar-gulcehre/) - [Deepak Narayanan](https://md.research.elamur.ai/free/en/authors/deepak-narayanan/) - [Razvan Pascanu](https://md.research.elamur.ai/free/en/authors/razvan-pascanu/) - [Samuel L Smith](https://md.research.elamur.ai/free/en/authors/samuel-l-smith/) - [Tri Dao](https://md.research.elamur.ai/free/en/authors/tri-dao/) - [Vijay Korthikanti](https://md.research.elamur.ai/free/en/authors/vijay-korthikanti/) - [Wonmin Byeon](https://md.research.elamur.ai/free/en/authors/wonmin-byeon/) ## Cited by Papers of our library cite their works 1,191 times (of the 149,439 papers whose bibliographies we read); [117 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/albert-gu/cited-by/). Updated 2 November 2026