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We present a method for automatically constructing a concept hierarchy for a given domain by querying a large language model.
Language models are few-shot learners,
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The curious case of neural text degeneration,
A. Holtzman, J. Buys, M. Forbes, Y. Choi, · 1904
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An empirical analysis of optimization techniques for terminological representation systems, or: Making KRIS get a move on,
F. Baader, B. Hollunder, B. Nebel, H. Profitlich, E. Franconi, · 1992
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Completing description logic knowledge bases using formal concept analysis,
F. Baader, B. Ganter, B. Sertkaya, U. Sattler, · 2007
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Supporting lexical ontology learning by relational exploration,
S. Rudolph, J. Völker, P. Hitzler, · 2007
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A novel approach to ontology classification,
B. Glimm, I. Horrocks, B. Motik, R. D. C. Shearer, G. Stoilos, · 2011
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Exact learning of lightweight description logic ontologies,
B. Konev, C. Lutz, A. Ozaki, F. Wolter, · 2017
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Language models as knowledge bases?,
F. Petroni, T. Rocktäschel, S. Riedel, P. S. H. Lewis, A. Bakhtin, Y. Wu, A. H. Miller, · 2019
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Learning description logic ontologies: Five approaches. where do they stand?,
A. Ozaki, · 2020
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Autoprompt: Eliciting knowledge from language models with automatically generated prompts,
T. Shin, Y. Razeghi, R. L. L. IV, E. Wallace, S. Singh, · 2020
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How much knowledge can you pack into the parameters of a language model?,
A. Roberts, C. Raffel, N. Shazeer, · 2020
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Concept placement using bert trained by transforming and summarizing biomedical ontology structure,
H. Liu, Y. Perl, J. Geller, · 2020
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Scaling language models: Methods, analysis & insights from training gopher,
J. W. Rae, S. Borgeaud, T. Cai, K. Millican, J. Hoffmann, H. F. Song, J. Aslanides, S. Henderson, R. Ring, S. Young, E. Rutherford, T. Hennigan, J. Menick, A. Cassirer, R. Powell, G. van den Driessche, L. A. Hendricks, M. Rauh, P. Huang, A. Glaese, J. Welbl, S. Dathathri, S. Huang, J. Uesato, J. Mellor, I. Higgins, A. Creswell, N. McAleese, A. Wu, E. Elsen, S. M. Jayakumar, E. Buchatskaya, D. Budden, E. Sutherland, K. Simonyan, M. Paganini, L. Sifre, L. Martens, X. L. Li, A. Kuncoro, A. Nematzadeh, E. Gribovskaya, D. Donato, A. Lazaridou, A. Mensch, J. Lespiau, M. Tsimpoukelli, N. Grigorev, D. Fritz, T. Sottiaux, M. Pajarskas, T. Pohlen, Z. Gong, D. Toyama, C. de Masson d’Autume, Y. Li, T. Terzi, V. Mikulik, I. Babuschkin, A. Clark, D. de Las Casas, A. Guy, C. Jones, J. Bradbury, M. J. Johnson, B. A. Hechtman, L. Weidinger, I. Gabriel, W. Isaac, E. Lockhart, S. Osindero, L. Rimell, C. Dyer, O. Vinyals, K. Ayoub, J. Stanway, L. Bennett, D. Hassabis, K. Kavukcuoglu, G. Irving, · 2021
Toward a comparison framework for interactive ontology enrichment methodologies,
J. Vrolijk, I. Reklos, M. Vafaie, A. Massari, M. Mohammadi, S. Rudolph, · 2022
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Palm: Scaling language modeling with pathways,
A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, P. Schuh, K. Shi, S. Tsvyashchenko, J. Maynez, A. Rao, P. Barnes, Y. Tay, N. Shazeer, V. Prabhakaran, E. Reif, N. Du, B. Hutchinson, R. Pope, J. Bradbury, J. Austin, M. Isard, G. Gur-Ari, P. Yin, T. Duke, A. Levskaya, S. Ghemawat, S. Dev, H. Michalewski, X. Garcia, V. Misra, K. Robinson, L. Fedus, D. Zhou, D. Ippolito, D. Luan, H. Lim, B. Zoph, A. Spiridonov, R. Sepassi, D. Dohan, S. Agrawal, M. Omernick, A. M. Dai, T. S. Pillai, M. Pellat, A. Lewkowycz, E. Moreira, R. Child, O. Polozov, K. Lee, Z. Zhou, X. Wang, B. Saeta, M. Diaz, O. Firat, M. Catasta, J. Wei, K. Meier-Hellstern, D. Eck, J. Dean, S. Petrov, N. Fiedel, · 2022
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S. Smith, M. Patwary, B. Norick, P. LeGresley, S. Rajbhandari, J. Casper, Z. Liu, S. Prabhumoye, G. Zerveas, V. Korthikanti, E. Zheng, R. Child, R. Y. Aminabadi, J. Bernauer, X. Song, M. Shoeybi, Y. He, M. Houston, S. Tiwary, B. Catanzaro, · 2022
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Learning how to ask: Querying lms with mixtures of soft prompts,
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Bertese: Learning to speak to BERT,
A. Haviv, J. Berant, A. Globerson, · 2021
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Experimental evidence for scale-induced category convergence across populations,
D. Guilbeault, A. Baronchelli, D. Centola, · 2021
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Calibrate before use: Improving few-shot performance of language models,
Z. Zhao, E. Wallace, S. Feng, D. Klein, S. Singh, · 2021
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Surface form competition: Why the highest probability answer isn’t always right,
A. Holtzman, P. West, V. Shwartz, Y. Choi, L. Zettlemoyer, · 2021
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D. Alivanistos, S. B. Santamaría, M. Cochez, J. Kalo, E. van Krieken, T. Thanapalasingam, · 2022
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Crawling the internal knowledge-base of language models,
R. Cohen, M. Geva, J. Berant, A. Globerson, · 2023
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Evaluating language models for knowledge base completion,
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Survey of hallucination in natural language generation,
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