HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
Integrity signals
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Hyena and HyenaDNA claimed to leverage up to 1M context, but their experiments trained on proportionally more data at longer contexts, making it hard to conclude if quality improvements at 1M context are due to context length or due to more data and computation.
“Hyena and HyenaDNA (Nguyen, Poli, et al. 2023;Poli et al. 2023), which claimed to leverage up to 1M context.However, their experiments trained on proportionally more data at longer contexts, making it hard to conclude if quality improvements at 1M context are due to context length or due to more data and computation.”
From Mamba: Linear-Time Sequence Modeling with Selective State Spaces (2023) · cites this paper as Nguyen, Poli, et al. 2023
Cited by
Sorted by citations
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Gu, A., & Dao, T. (2023) · arXiv · doi:10.48550/arxiv.2312.00752 · Cited by 1,579 · see citing works
Nucleotide Transformer: building and evaluating robust foundation models for human genomics
Dalla-Torre, H., Gonzalez, L., Mendoza-Revilla, J., Lopez Carranza, N., Grzywaczewski, A. H., Oteri, F., Dallago, C., Trop, E., de Almeida, B. P., Sirelkhatim, H., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02523-z · Cited by 656 · see citing works
Sequence modeling and design from molecular to genome scale with Evo
Nguyen, E., Poli, M., Durrant, M. G., Kang, B., Katrekar, D., Li, D. B., Bartie, L. J., Thomas, A. W., King, S. H., Brixi, G., et al. (2024) · Science · doi:10.1126/science.ado9336 · Cited by 580 · see citing works
Self-citationTitans: Learning to Memorize at Test Time
Behrouz, A., Zhong, P., & Mirrokni, V. (2025) · arXiv · doi:10.48550/arxiv.2501.00663 · Cited by 24 · see citing works
Zoology: Measuring and Improving Recall in Efficient Language Models
Arora, S., Eyuboglu, S., Timalsina, A., Johnson, I., Poli, M., Zou, J., Rudra, A., & Ré, C. (2023) · arXiv · doi:10.48550/arxiv.2312.04927 · Cited by 4 · see citing works
Self-citation
- Authors
- Nguyen, E., Poli, M., Faizi, M., Thomas, A., Wornow, M., Birch-Sykes, C., Massaroli, S., Patel, A., Rabideau, C., Bengio, Y., Ermon, S., Ré, C., & Baccus, S.
- ORCID
- Venue
- Advances in Neural Information Processing Systems 36
- Published
- 2023
- Pages
- 43177-43201
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133235585
- Cited by
- 66
- References
- 0
- Citations by year
- 2026: 64 · 2025: 1 · 2023: 1
- FWCI
- 75.82
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- single-nucleotide resolution, DNA sequence prediction, long-range dependencies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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