Fetching the paper…
Reading the bibliography…
The parallels between protein sequences and natural language in their sequential structures have inspired the application of large language models (LLMs) to protein understanding.
CATH – a hierarchic classification of protein domain structures
C. Orengo, A. Michie, S. Jones, D. Jones, M. Swindells, and J. Thornton · 1997
Earlier work this paper cites.
Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation
N. A. O’Leary, M. W. Wright, J. R. Brister, S. Ciufo, D. Haddad, R. McVeigh, B. Rajput, B. Robbertse, B. Smith-White, D. Ako-Adjei, A. Astashyn, A. Badretdin, Y. Bao, O. Blinkova, V. Brover, V. Chetvernin, J. Choi, E. Cox, O. Ermolaeva, C. M. Farrell, T. Goldfarb, T. Gupta, D. Haft, E. Hatcher, W. Hlavina, V. S. Joardar, V. K. Kodali, W. Li, D. Maglott, P. Masterson, K. M. McGarvey, M. R. Murphy, K. O’Neill, S. Pujar, S. H. Rangwala, D. Rausch, L. D. Riddick, C. Schoch, A. Shkeda, S. S. Storz, H. Sun, F. Thibaud-Nissen, I. Tolstoy, R. E. Tully, A. R. Vatsan, C. Wallin, D. Webb, W. Wu, M. J. Landrum, A. Kimchi, T. Tatusova, M. DiCuccio, P. Kitts, T. D. Murphy, and K. D. Pruitt · 2015
Earlier work this paper cites.
Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
S. Narayan, S. B. Cohen, and M. Lapata · 2018
Earlier work this paper cites.
Know What You Don’t Know: Unanswerable Questions for SQuAD
P. Rajpurkar, R. Jia, and P. Liang · 2018
Earlier work this paper cites.
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
A. Rives, J. Meier, T. Sercu, S. Goyal, Z. Lin, J. Liu, D. Guo, M. Ott, C. L. Zitnick, J. Ma, and R. Fergus · 2019
Earlier work this paper cites.
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)
A. W. Senior, R. Evans, J. Jumper, J. Kirkpatrick, L. Sifre, T. Green, C. Qin, A. Žídek, A. W. R. Nelson, A. Bridgland, H. Penedones, S. Petersen, K. Simonyan, S. Crossan, P. Kohli, D. T. Jones, D. Silver, K. Kavukcuoglu, and D. Hassabis · 2019
Earlier work this paper cites.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
A. Wang, A. Singh, J. Michael, F. Hill, O. Levy, and S. R. Bowman · 2019
Earlier work this paper cites.
The InterPro protein families and domains database: 20 years on
M. Blum, H.-Y. Chang, S. Chuguransky, T. Grego, S. Kandasaamy, A. Mitchell, G. Nuka, T. Paysan-Lafosse, M. Qureshi, S. Raj, L. Richardson, G. A. Salazar, L. Williams, P. Bork, A. Bridge, J. Gough, D. H. Haft, I. Letunic, A. Marchler-Bauer, H. Mi, D. A. Natale, M. Necci, C. A. Orengo, A. P. Pandurangan, C. Rivoire, C. J. A. Sigrist, I. Sillitoe, N. Thanki, P. D. Thomas, S. C. E. Tosatto, C. H. Wu, A. Bateman, and R. D. Finn · 2020
Earlier work this paper cites.
RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences
S. K. Burley, C. Bhikadiya, C. Bi, S. Bittrich, L. Chen, G. V. Crichlow, C. H. Christie, K. Dalenberg, L. Di Costanzo, J. M. Duarte, S. Dutta, Z. Feng, S. Ganesan, D. S. Goodsell, S. Ghosh, R. K. Green, V. Guranović, D. Guzenko, B. P. Hudson, C. Lawson, Y. Liang, R. Lowe, H. Namkoong, E. Peisach, I. Persikova, C. Randle, A. Rose, Y. Rose, A. Sali, J. Segura, M. Sekharan, C. Shao, Y.-P. Tao, M. Voigt, J. Westbrook, J. Y. Young, C. Zardecki, and M. Zhuravleva · 2020
Earlier work this paper cites.
The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets
D. Szklarczyk, A. L. Gable, K. C. Nastou, D. Lyon, R. Kirsch, S. Pyysalo, N. T. Doncheva, M. Legeay, T. Fang, P. Bork, L. J. Jensen, and C. von Mering · 2020
Earlier work this paper cites.
Measuring massive multitask language understanding
D. Hendrycks, C. Burns, S. Basart, A. Zou, M. Mazeika, D. Song, and J. Steinhardt · 2021
Earlier work this paper cites.
Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14)
L. Kinch, R. Schaeffer, A. Kryshtafovych, and N. Grishin · 2021
Earlier work this paper cites.
Database resources of the national center for biotechnology information
E. W. Sayers, E. E. Bolton, J. R. Brister, K. Canese, J. Chan, D. C. Comeau, R. Connor, K. Funk, C. Kelly, S. Kim, T. Madej, A. Marchler-Bauer, C. Lanczycki, S. Lathrop, Z. Lu, F. Thibaud-Nissen, T. Murphy, L. Phan, Y. Skripchenko, T. Tse, J. Wang, R. Williams, B. W. Trawick, K. D. Pruitt, and S. T. Sherry · 2021
Cited alongside, same era.
Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension
S. Xu, Y. Liu, X. Yi, S. Zhou, H. Li, and Y. Wu · 2021
Cited alongside, same era.
UniProt: the Universal Protein Knowledgebase in 2023
T. U. Consortium · 2022
Cited alongside, same era.
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Z. Du, Y. Qian, X. Liu, M. Ding, J. Qiu, Z. Yang, and J. Tang · 2022
Cited alongside, same era.
KEGG for taxonomy-based analysis of pathways and genomes
M. Kanehisa, M. Furumichi, Y. Sato, M. Kawashima, and M. Ishiguro-Watanabe · 2022
Cited alongside, same era.
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
Y. Huang, Y. Bai, Z. Zhu, J. Zhang, J. Zhang, T. Su, J. Liu, C. Lv, Y. Zhang, j. lei, Y. Fu, M. Sun, and J. He · 2023
Later among the works it cites.
A. Q. Jiang, A. Sablayrolles, A. Mensch, C. Bamford, D. S. Chaplot, D. de las Casas, F. Bressand, G. Lengyel, G. Lample, L. Saulnier, L. R. Lavaud, M.-A. Lachaux, P. Stock, T. L. Scao, T. Lavril, T. Wang, T. Lacroix, and W. E. Sayed · 2023
Later among the works it cites.
Holistic Evaluation of Language Models
P. Liang, R. Bommasani, T. Lee, D. Tsipras, D. Soylu, M. Yasunaga, Y. Zhang, D. Narayanan, Y. Wu, A. Kumar, B. Newman, B. Yuan, B. Yan, C. Zhang, C. A. Cosgrove, C. D. Manning, C. Re, D. Acosta-Navas, D. A. Hudson, E. Zelikman, E. Durmus, F. Ladhak, F. Rong, H. Ren, H. Yao, J. WANG, K. Santhanam, L. Orr, L. Zheng, M. Yuksekgonul, M. Suzgun, N. Kim, N. Guha, N. S. Chatterji, O. Khattab, P. Henderson, Q. Huang, R. A. Chi, S. M. Xie, S. Santurkar, S. Ganguli, T. Hashimoto, T. Icard, T. Zhang, V. Chaudhary, W. Wang, X. Li, Y. Mai, Y. Zhang, and Y. Koreeda · 2023
Later among the works it cites.
Llama 2: Open Foundation and Fine-Tuned Chat Models
H. Touvron, L. Martin, K. Stone, P. Albert, A. Almahairi, Y. Babaei, N. Bashlykov, S. Batra, P. Bhargava, S. Bhosale, D. Bikel, L. Blecher, C. C. Ferrer, M. Chen, G. Cucurull, D. Esiobu, J. Fernandes, J. Fu, W. Fu, B. Fuller, C. Gao, V. Goswami, N. Goyal, A. Hartshorn, S. Hosseini, R. Hou, H. Inan, M. Kardas, V. Kerkez, M. Khabsa, I. Kloumann, A. Korenev, P. S. Koura, M.-A. Lachaux, T. Lavril, J. Lee, D. Liskovich, Y. Lu, Y. Mao, X. Martinet, T. Mihaylov, P. Mishra, I. Molybog, Y. Nie, A. Poulton, J. Reizenstein, R. Rungta, K. Saladi, A. Schelten, R. Silva, E. M. Smith, R. Subramanian, X. E. Tan, B. Tang, R. Taylor, A. Williams, J. X. Kuan, P. Xu, Z. Yan, I. Zarov, Y. Zhang, A. Fan, M. Kambadur, S. Narang, A. Rodriguez, R. Stojnic, S. Edunov, and T. Scialom · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
LAION-5B: an open large-scale dataset for training next generation image-text models
C. Schuhmann, R. Beaumont, R. Vencu, C. Gordon, R. Wightman, M. Cherti, T. Coombes, A. Katta, C. Mullis, M. Wortsman, et al · 2022
Cited alongside, same era.
BERN2: an advanced neural biomedical named entity recognition and normalization tool
M. Sung, M. Jeong, Y. Choi, D. Kim, J. Lee, and J. Kang · 2022
Cited alongside, same era.
Chain of thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, brian ichter, F. Xia, E. H. Chi, Q. V. Le, and D. Zhou · 2022
Cited alongside, same era.
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding
M. Xu, Z. Zhang, J. Lu, Z. Zhu, Y. Zhang, M. Chang, R. Liu, and J. Tang · 2022
Cited alongside, same era.
The Falcon Series of Open Language Models
E. Almazrouei, H. Alobeidli, A. Alshamsi, A. Cappelli, R. Cojocaru, M. Debbah, Étienne Goffinet, D. Hesslow, J. Launay, Q. Malartic, D. Mazzotta, B. Noune, B. Pannier, and G. Penedo · 2023
Cited alongside, same era.
J. Bai, S. Bai, Y. Chu, Z. Cui, K. Dang, X. Deng, Y. Fan, W. Ge, Y. Han, F. Huang, B. Hui, L. Ji, M. Li, J. Lin, R. Lin, D. Liu, G. Liu, C. Lu, K. Lu, J. Ma, R. Men, X. Ren, X. Ren, C. Tan, S. Tan, J. Tu, P. Wang, S. Wang, W. Wang, S. Wu, B. Xu, J. Xu, A. Yang, H. Yang, J. Yang, S. Yang, Y. Yao, B. Yu, H. Yuan, Z. Yuan, J. Zhang, X. Zhang, Y. Zhang, Z. Zhang, C. Zhou, J. Zhou, X. Zhou, and T. Zhu · 2023
Cited alongside, same era.
Baichuan 2: Open large-scale language models
Baichuan · 2023
Cited alongside, same era.
Later among the works it cites.
ProtST: Multi-modality learning of protein sequences and biomedical texts
M. Xu, X. Yuan, S. Miret, and J. Tang · 2023
Later among the works it cites.
Protein representation learning via knowledge enhanced primary structure reasoning
H.-Y. Zhou, Y. Fu, Z. Zhang, B. Cheng, and Y. Yu · 2023
Later among the works it cites.
Yi: Open Foundation Models by 01.AI
01.AI, :, A. Young, B. Chen, C. Li, C. Huang, G. Zhang, G. Zhang, H. Li, J. Zhu, J. Chen, J. Chang, K. Yu, P. Liu, Q. Liu, S. Yue, S. Yang, S. Yang, T. Yu, W. Xie, W. Huang, X. Hu, X. Ren, X. Niu, P. Nie, Y. Xu, Y. Liu, Y. Wang, Y. Cai, Z. Gu, Z. Liu, and Z. Dai · 2024
Closest in time.
Z. Cai, M. Cao, H. Chen, K. Chen, K. Chen, X. Chen, X. Chen, Z. Chen, Z. Chen, P. Chu, X. Dong, H. Duan, Q. Fan, Z. Fei, Y. Gao, J. Ge, C. Gu, Y. Gu, T. Gui, A. Guo, Q. Guo, C. He, Y. Hu, T. Huang, T. Jiang, P. Jiao, Z. Jin, Z. Lei, J. Li, J. Li, L. Li, S. Li, W. Li, Y. Li, H. Liu, J. Liu, J. Hong, K. Liu, K. Liu, X. Liu, C. Lv, H. Lv, K. Lv, L. Ma, R. Ma, Z. Ma, W. Ning, L. Ouyang, J. Qiu, Y. Qu, F. Shang, Y. Shao, D. Song, Z. Song, Z. Sui, P. Sun, Y. Sun, H. Tang, B. Wang, G. Wang, J. Wang, J. Wang, R. Wang, Y. Wang, Z. Wang, X. Wei, Q. Weng, F. Wu, Y. Xiong, C. Xu, R. Xu, H. Yan, Y. Yan, X. Yang, H. Ye, H. Ying, J. Yu, J. Yu, Y. Zang, C. Zhang, L. Zhang, P. Zhang, P. Zhang, R. Zhang, S. Zhang, S. Zhang, W. Zhang, W. Zhang, X. Zhang, X. Zhang, H. Zhao, Q. Zhao, X. Zhao, F. Zhou, Z. Zhou, J. Zhuo, Y. Zou, X. Qiu, Y. Qiao, and D. Lin · 2024
Closest in time.
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models
Y. Fang, X. Liang, N. Zhang, K. Liu, R. Huang, Z. Chen, X. Fan, and H. Chen · 2024
Closest in time.
Retrieval-augmented generation for large language models: A survey
Y. Gao et al · 2024
Closest in time.
OpenAI et al · 2024
Closest in time.
Moonshot: Towards controllable video generation and editing with multimodal conditions
D. J. Zhang, D. Li, H. Le, M. Z. Shou, C. Xiong, and D. Sahoo · 2024
Closest in time.