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Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including healthcare, finance, transportation, and education.
Language models are few-shot learners, in: Proceedings of the 34th International Conference on Neural Information Processing Systems, pp. 1877–1901
Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al., 2020b · 1901
Earlier work this paper cites.
Alreshidi, E., 2019 · 1906
Earlier work this paper cites.
Learning to few-shot learn across diverse natural language classification tasks
Bansal, T., Jha, R., McCallum, A., 2019 · 1911
Earlier work this paper cites.
A deep learning model for detecting cage-free hens on the litter floor
Yang, X., Chai, L., Bist, R.B., Subedi, S., Wu, Z., 2022 · 1983
Earlier work this paper cites.
Learning from one example through shared densities on transforms, in: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, pp. 464–471
Miller, E.G., Matsakis, N.E., Viola, P.A., 2000 · 2000
Earlier work this paper cites.
Finding berries: Segmentation and counting of cranberries using point supervision and shape priors
Akiva, P., Dana, K., Oudemans, P., Mars, M., 2020 · 2004
Earlier work this paper cites.
Weakly supervised learning guided by activation mapping applied to a novel citrus pest benchmark
Bollis, E., Pedrini, H., Avila, S., 2020 · 2004
Earlier work this paper cites.
Object classification from a single example utilizing class relevance metrics
Fink, M., 2004 · 2004
Earlier work this paper cites.
One-shot learning of object categories
Fei-Fei, L., Fergus, R., Perona, P., 2006 · 2006
Earlier work this paper cites.
Dbpedia: A nucleus for a web of open data, in: The semantic web, pp. 722–735
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z., 2007 · 2007
Earlier work this paper cites.
Autocount: Unsupervised segmentation and counting of organs in field images
Ubbens, J., Ayalew, T., Shirtliffe, S., Josuttes, A., Pozniak, C., Stavness, I., 2020 · 2007
Earlier work this paper cites.
Introduction to information retrieval. volume 39
Schütze, H., Manning, C.D., Raghavan, P., 2008 · 2008
Earlier work this paper cites.
Linkedgeodata: Adding a spatial dimension to the web of data, in: 8th International Semantic Web Conference on The Semantic Web-ISWC, pp. 731–746
Auer, S., Lehmann, J., Hellmann, S., 2009 · 2009
Earlier work this paper cites.
Linked data: The story so far, in: Semantic services, interoperability and web applications: emerging concepts, pp. 205–227
Bizer, C., Heath, T., Berners-Lee, T., 2011 · 2011
Earlier work this paper cites.
One-shot learning with a hierarchical nonparametric bayesian model, in: Proceedings of ICML Workshop on Unsupervised and Transfer Learning, pp. 195–206
Salakhutdinov, R., Tenenbaum, J., Torralba, A., 2012 · 2012
Earlier work this paper cites.
Wikidata: A new platform for collaborative data collection, in: Proceedings of the 21st international conference on world wide web, pp. 1063–1064
Vrandečić, D., 2012 · 2012
Earlier work this paper cites.
Assessment of the accuracy of geonames gazetteer data, in: Proceedings of the 7th workshop on geographic information retrieval, pp. 74–81
Ahlers, D., 2013 · 2013
Earlier work this paper cites.
In search of the behavioural correlates of optical flow patterns in the automated assessment of broiler chicken welfare
Dawkins, M.S., Cain, R., Merelie, K., Roberts, S.J., 2013 · 2013
Earlier work this paper cites.
One-shot adaptation of supervised deep convolutional models
Hoffman, J., Tzeng, E., Donahue, J., Jia, Y., Saenko, K., Darrell, T., 2013 · 2013
Earlier work this paper cites.
Knowledge vault: A web-scale approach to probabilistic knowledge fusion, in: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 601–610
Dong, X., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., Murphy, K., Strohmann, T., Sun, S., Zhang, W., 2014 · 2014
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation, in: International conference on machine learning, pp. 1180–1189
Ganin, Y., Lempitsky, V., 2015 · 2015
Earlier work this paper cites.
Human-level concept learning through probabilistic program induction
Lake, B.M., Salakhutdinov, R., Tenenbaum, J.B., 2015 · 2015
Earlier work this paper cites.
Localize me anywhere, anytime: a multi-task point-retrieval approach, in: Proceedings of the IEEE International Conference on Computer Vision, pp. 2434–2442
Lu, G., Yan, Y., Ren, L., Song, J., Sebe, N., Kambhamettu, C., 2015 · 2015
Earlier work this paper cites.
Learning to learn by gradient descent by gradient descent
Andrychowicz, M., Denil, M., Gomez, S., Hoffman, M.W., Pfau, D., Schaul, T., Shillingford, B., De Freitas, N., 2016 · 2016
Earlier work this paper cites.
Image style transfer using convolutional neural networks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2414–2423
Gatys, L.A., Ecker, A.S., Bethge, M., 2016 · 2016
Earlier work this paper cites.
Deep Learning
Goodfellow, I., Bengio, Y., Courville, A., 2016 · 2016
Earlier work this paper cites.
Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770–778
He, K., Zhang, X., Ren, S., Sun, J., 2016 · 2016
Earlier work this paper cites.
One-shot generalization in deep generative models , arXiv:1603.05106
Jimenez Rezende, D., Mohamed, S., Danihelka, I., Gregor, K., Wierstra, D., 2016 · 2016
Earlier work this paper cites.
One-shot learning of scene locations via feature trajectory transfer, in: IEEE conference on computer vision and pattern recognition, pp. 78–86
Kwitt, R., Hegenbart, S., Niethammer, M., 2016 · 2016
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Qi, C.R., Su, H., Mo, K., Guibas, L.J., 2016 · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 779–788
Redmon, J., Divvala, S., Girshick, R., Farhadi, A., 2016 · 2016
Earlier work this paper cites.
Meta-learning with memory-augmented neural networks, in: International conference on machine learning, pp. 1842–1850
Santoro, A., Bartunov, S., Botvinick, M., Wierstra, D., Lillicrap, T., 2016 · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D., 2016 · 2016
Earlier work this paper cites.
Open set domain adaptation, in: IEEE International Conference on Computer Vision (ICCV), pp. 754–763
Busto, P.P., Gall, J., 2017 · 2017
Earlier work this paper cites.
One-shot video object segmentation, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 221–230
Caelles, S., Maninis, K.K., Pont-Tuset, J., Leal-Taixé, L., Cremers, D., Van Gool, L., 2017 · 2017
Earlier work this paper cites.
A survey on dialogue systems: Recent advances and new frontiers
Chen, H., Liu, X., Yin, D., Tang, J., 2017 · 2017
Earlier work this paper cites.
Domain adaptation for visual applications: A comprehensive survey
Csurka, G., 2017 · 2017
Earlier work this paper cites.
Mask r-cnn, in: Proceedings of the IEEE international conference on computer vision, pp. 2961–2969
He, K., Gkioxari, G., Dollár, P., Girshick, R., 2017 · 2017
Earlier work this paper cites.
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision, in: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp. 23–33
Liang, C., Berant, J., Le, Q., Forbus, K., Lao, N., 2017 · 2017
Earlier work this paper cites.
Few-shot adversarial domain adaptation
Motiian, S., Jones, Q., Iranmanesh, S., Doretto, G., 2017 · 2017
Earlier work this paper cites.
Optimization as a model for few-shot learning, in: International conference on learning representations
Ravi, S., Larochelle, H., 2017 · 2017
Earlier work this paper cites.
Attentive recurrent comparators, in: International conference on machine learning, pp. 3173–3181
Shyam, P., Gupta, S., Dukkipati, A., 2017 · 2017
Earlier work this paper cites.
Attention is all you need, in: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 6000–6010
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I., 2017 · 2017
Earlier work this paper cites.
Simple online and realtime tracking with a deep association metric, in: IEEE international conference on image processing (ICIP), pp. 3645–3649
Wojke, N., Bewley, A., Paulus, D., 2017 · 2017
Earlier work this paper cites.
Machine learning on big data: Opportunities and challenges
Zhou, L., Pan, S., Wang, J., Vasilakos, A.V., 2017 · 2017
Earlier work this paper cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks, in: IEEE International Conference on Computer Vision (ICCV)
Zhu, J.Y., Park, T., Isola, P., Efros, A.A., 2017 · 2017
Earlier work this paper cites.
Multi-content gan for few-shot font style transfer, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 7564–7573
Azadi, S., Fisher, M., Kim, V.G., Wang, Z., Shechtman, E., Darrell, T., 2018 · 2018
Earlier work this paper cites.
Graph-to-sequence learning using gated graph neural networks, in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 273–283
Beck, D., Haffari, G., Cohn, T., 2018 · 2018
Earlier work this paper cites.
One-shot unsupervised cross domain translation
Benaim, S., Wolf, L., 2018 · 2018
Earlier work this paper cites.
Mitigating particulate matter emissions of a commercial cage-free aviary hen house, in: 2018 ASABE Annual International Meeting, p. 1
Chai, L., Xin, H., Wang, Y., Oliveira, J., Wang, K., Zhao, Y., 2018 · 2018
Earlier work this paper cites.
Foodon: a harmonized food ontology to increase global food traceability, quality control and data integration
Dooley, D.M., Griffiths, E.J., Gosal, G.S., Buttigieg, P.L., Hoehndorf, R., Lange, M.C., Schriml, L.M., Brinkman, F.S., Hsiao, W.W., 2018 · 2018
Earlier work this paper cites.
Real-time monitoring of broiler flock’s welfare status using camera-based technology
Fernandez, A.P., Norton, T., Tullo, E., van Hertem, T., Youssef, A., Exadaktylos, V., Vranken, E., Guarino, M., Berckmans, D., 2018 · 2018
Earlier work this paper cites.
Extending a parser to distant domains using a few dozen partially annotated examples
Joshi, V., Peters, M., Hopkins, M., 2018 · 2018
Earlier work this paper cites.
Clear: Cumulative learning for one-shot one-class image recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3446–3455
Kozerawski, J., Turk, M., 2018 · 2018
Earlier work this paper cites.
A review on deep learning techniques applied to answer selection, in: Proceedings of the 27th International Conference on Computational Linguistics, pp. 2132–2144
Lai, T., Bui, T., Li, S., 2018 · 2018
Earlier work this paper cites.
Conditional adversarial domain adaptation
Long, M., Cao, Z., Wang, J., Jordan, M.I., 2018 · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I., et al., 2018 · 2018
Earlier work this paper cites.
Gnis-ld: Serving and visualizing the geographic names information system gazetteer as linked data, in: European Semantic Web Conference, pp. 528–540
Regalia, B., Janowicz, K., Mai, G., Varanka, D., Usery, E.L., 2018 · 2018
Earlier work this paper cites.
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Schwartz, E., Karlinsky, L., Shtok, J., Harary, S., Marder, M., Kumar, A., Feris, R., Giryes, R., Bronstein, A., 2018 · 2018
Earlier work this paper cites.
A dirt-t approach to unsupervised domain adaptation
Shu, R., Bui, H.H., Narui, H., Ermon, S., 2018 · 2018
Earlier work this paper cites.
Open domain question answering using early fusion of knowledge bases and text, in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4231–4242
Sun, H., Dhingra, B., Zaheer, M., Mazaitis, K., Salakhutdinov, R., Cohen, W., 2018 · 2018
Earlier work this paper cites.
Conversational recommender system, in: The 41st international acm sigir conference on research & development in information retrieval, pp. 235–244
Sun, Y., Zhang, Y., 2018 · 2018
Earlier work this paper cites.
Learning to compare: Relation network for few-shot learning, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1199–1208
Sung, F., Yang, Y., Zhang, L., Xiang, T., Torr, P.H.S., Hospedales, T.M., 2018 · 2018
Earlier work this paper cites.
Dkn: Deep knowledge-aware network for news recommendation, in: Proceedings of the 2018 world wide web conference, pp. 1835–1844
Wang, H., Zhang, F., Xie, X., Guo, M., 2018 · 2018
Cited alongside, same era.
Deep visual domain adaptation: A survey
Wang, M., Deng, W., 2018 · 2018
Cited alongside, same era.
Unsupervised domain adaptation: An adaptive feature norm approach
Xu, R., Li, G., Yang, J., Lin, L., 2018 · 2018
Cited alongside, same era.
Fine-grained visual categorization using meta-learning optimization with sample selection of auxiliary data, in: Proceedings of the european conference on computer vision (ECCV), pp. 233–248
Zhang, Y., Tang, H., Jia, K., 2018 · 2018
Cited alongside, same era.
Commonsense knowledge aware conversation generation with graph attention, in: IJCAI, pp. 4623–4629
Zhou, H., Young, T., Huang, M., Zhao, H., Xu, J., Zhu, X., 2018 · 2018
Regenerative agriculture and integrative permaculture for sustainable and technology driven global food production and security
McLennon, E., Dari, B., Jha, G., Sihi, D., Kankarla, V., 2021 · 2021
Later among the works it cites.
Competitive strategies of personnel management in business processes of agricultural enterprises focused on digitalization
Mykhailichenko, M., Lozhachevska, O., Smagin, V., Krasnoshtan, O., Zos-Kior, M., Hnatenko, I., 2021 · 2021
Later among the works it cites.
Edge: Enriching knowledge graph embeddings with external text, in: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2767–2776
Rezayi, S., Zhao, H., Kim, S., Rossi, R., Lipka, N., Li, S., 2021 · 2021
Later among the works it cites.
Text based smart answering system in agriculture using rnn, in: Proceedings of the 18th International Conference on Natural Language Processing (ICON), pp. 663–669
Sukumar, R., Hemalatha, N., Sarin, S., CA, R.M., 2021 · 2021
Later among the works it cites.
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Cited alongside, same era.
Weakly supervised fruit counting for yield estimation using spatial consistency
Bellocchio, E., Ciarfuglia, T.A., Costante, G., Valigi, P., 2019 · 2019
Cited alongside, same era.
Transgcn: Coupling transformation assumptions with graph convolutional networks for link prediction, in: Proceedings of the 10th international conference on knowledge capture, pp. 131–138
Cai, L., Yan, B., Mai, G., Janowicz, K., Zhu, R., 2019 · 2019
Cited alongside, same era.
Agrikg: an agricultural knowledge graph and its applications, in: Database Systems for Advanced Applications: DASFAA 2019 International Workshops: BDMS, BDQM, and GDMA, Chiang Mai, Thailand, April 22–25, 2019, Proceedings 24, pp. 533–537
Chen, Y., Kuang, J., Cheng, D., Zheng, J., Gao, M., Zhou, A., 2019 · 2019
Cited alongside, same era.
Scalable and ligthway bio-inspired coordination protocol for fanet in precision agriculture applications
De Rango, F., Potrino, G., Tropea, M., Santamaria, A.F., Fazio, P., 2019 · 2019
Cited alongside, same era.
A weakly supervised deep learning framework for sorghum head detection and counting
Ghosal, S., Zheng, B., Chapman, S.C., Potgieter, A.B., Jordan, D.R., Wang, X., Singh, A.K., Singh, A., Hirafuji, M., Ninomiya, S., Ganapathysubramanian, B., Sarkar, S., Guo, W., 2019 · 2019
Cited alongside, same era.
Leaf counting without annotations using adversarial unsupervised domain adaptation, in: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2590–2599
Giuffrida, M.V., Dobrescu, A., Doerner, P., Tsaftaris, S.A., 2019 · 2019
Cited alongside, same era.
Knowledge graph embedding based question answering, in: Proceedings of the twelfth ACM international conference on web search and data mining, pp. 105–113
Huang, X., Zhang, J., Li, D., Li, P., 2019 · 2019
Cited alongside, same era.
Agriculture development, pesticide application and its impact on the environment
Tudi, M., Daniel Ruan, H., Wang, L., Lyu, J., Sadler, R., Connell, D., Chu, C., Phung, D.T., 2021 · 2021
Later among the works it cites.
Cdtrans: Cross-domain transformer for unsupervised domain adaptation
Xu, T., Chen, W., Wang, P., Wang, F., Li, H., Jin, R., 2021 · 2021
Later among the works it cites.
Crossfit: A few-shot learning challenge for cross-task generalization in nlp
Ye, Q., Lin, B.Y., Ren, X., 2021 · 2021
Later among the works it cites.
A survey on multi-task learning
Zhang, Y., Yang, Q., 2021 · 2021
Later among the works it cites.
Domain generalization in vision: A survey
Zhou, K., Liu, Z., Qiao, Y., Xiang, T., Loy, C.C., 2021 · 2021
Later among the works it cites.
Self-supervised universal domain adaptation with adaptive memory separation, in: IEEE International Conference on Data Mining (ICDM), pp. 1547–1552
Zhu, R., Li, S., 2021 · 2021
Later among the works it cites.
The digitization of agricultural industry–a systematic literature review on agriculture 4.0
Abbasi, R., Martinez, P., Ahmad, R., 2022 · 2022
Later among the works it cites.
Supervised and weakly supervised deep learning for segmentation and counting of cotton bolls using proximal imagery
Adke, S., Li, C., Rasheed, K.M., Maier, F.W., 2022 · 2022
Later among the works it cites.
Towards applicability of machine learning techniques in agriculture and energy sector
Arumugam, K., Swathi, Y., Sanchez, D.T., Mustafa, M., Phoemchalard, C., Phasinam, K., Okoronkwo, E., 2022 · 2022
Later among the works it cites.
A systematic review of knowledge representation techniques in smart agriculture (urban)
Bhuyan, B.P., Tomar, R., Cherif, A.R., 2022 · 2022
Later among the works it cites.
Relationprompt: Leveraging prompts to generate synthetic data for zero-shot relation triplet extraction, in: Findings of the Association for Computational Linguistics: ACL 2022, pp. 45–57
Chia, Y.K., Bing, L., Poria, S., Si, L., 2022 · 2022
Later among the works it cites.
Monitoring behaviors of broiler chickens at different ages with deep learning
Guo, Y., Aggrey, S.E., Wang, P., Oladeinde, A., Chai, L., 2022 · 2022
Later among the works it cites.
Imagen video: High definition video generation with diffusion models
Ho, J., Chan, W., Saharia, C., Whang, J., Gao, R., Gritsenko, A., Kingma, D.P., Poole, B., Norouzi, M., Fleet, D.J., et al., 2022 · 2022
Later among the works it cites.
Weathergan: Unsupervised multi-weather image-to-image translation via single content-preserving uresnet generator
Hwang, S., Jeon, S., Ma, Y.S., Byun, H., 2022 · 2022
Later among the works it cites.
Know, know where, knowwheregraph: A densely connected, cross-domain knowledge graph and geo-enrichment service stack for applications in environmental intelligence
Janowicz, K., Hitzler, P., Li, W., Rehberger, D., Schildhauer, M., Zhu, R., Shimizu, C., Fisher, C., Cai, L., Mai, G., et al., 2022 · 2022
Later among the works it cites.
ultralytics/yolov5: v6.1 - tensorrt, tensorflow edge tpu and openvino export and inference
Jocher, G., Chaurasia, A., Stoken, A., Borovec, J., NanoCode012, Kwon, Y., TaoXie, Fang, J., et al., 2022 · 2022
Later among the works it cites.
Depthformer: A high-resolution depth-wise transformer for animal pose estimation
Liu, S., Fan, Q., Liu, S., Zhao, C., 2022 · 2022
Later among the works it cites.
Image-based localization for self-driving vehicles based on online network adjustment in a dynamic scope, in: International Joint Conference on Neural Networks (IJCNN), pp. 1–8
Lu, G., 2022 · 2022
Later among the works it cites.
Recognition and segmentation of individual pigs based on swin transformer
Lu, J., Wang, W., Zhao, K., Wang, H., 2022 · 2022
Later among the works it cites.
3d modeling beneath ground: Plant root detection and reconstruction based on ground-penetrating radar, in: IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 68–77
Lu, Y., Lu, G., 2022 · 2022
Later among the works it cites.
Applications of new technologies for monitoring and predicting grains quality stored: Sensors, internet of things, and artificial intelligence
Lutz, E., Coradi, P.C., 2022 · 2022
Later among the works it cites.
Towards a foundation model for geospatial artificial intelligence (vision paper), in: Proceedings of the 30th International Conference on Advances in Geographic Information Systems, pp. 1–4
Mai, G., Cundy, C., Choi, K., Hu, Y., Lao, N., Ermon, S., 2022 · 2022
Later among the works it cites.
Sdedit: Guided image synthesis and editing with stochastic differential equations, in: International Conference on Learning Representations
Meng, C., He, Y., Song, Y., Song, J., Wu, J., Zhu, J.Y., Ermon, S., 2022 · 2022
Later among the works it cites.
Review on knowledge extraction from text and scope in agriculture domain
Nismi Mol, E., Santosh Kumar, M., 2022 · 2022
Later among the works it cites.
Pesticide residues in food
Organization, W.H., · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al., 2022 · 2022
Later among the works it cites.
Weakly-supervised learning to automatically count cotton flowers from aerial imagery
Petti, D., Li, C., 2022 · 2022
Later among the works it cites.
Day-to-night image synthesis for training nighttime neural isps, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Punnappurath, A., Abuolaim, A., Abdelhamed, A., Levinshtein, A., Brown, M.S., 2022 · 2022
Later among the works it cites.
A joint model for entity and relation extraction based on bert
Qiao, B., Zou, Z., Huang, Y., Fang, K., Zhu, X., Chen, Y., 2022 · 2022
Later among the works it cites.
Robust speech recognition via large-scale weak supervision
Radford, A., Kim, J.W., Xu, T., Brockman, G., McLeavey, C., Sutskever, I., 2022 · 2022
Later among the works it cites.
Agribert: knowledge-infused agricultural language models for matching food and nutrition, IJCAI
Rezayi, S., Liu, Z., Wu, Z., Dhakal, C., Ge, B., Zhen, C., Liu, T., Li, S., 2022 · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B., 2022 · 2022
Later among the works it cites.
Bloom: A 176b-parameter open-access multilingual language model
Scao, T.L., Fan, A., Akiki, C., Pavlick, E., Ilić, S., Hesslow, D., Castagné, R., Luccioni, A.S., Yvon, F., Gallé, M., et al., 2022 · 2022
Later among the works it cites.
Climategan: Raising climate change awareness by generating images of floods, in: International Conference on Learning Representations
Schmidt, V., Luccioni, A., Teng, M., Zhang, T., Reynaud, A., Raghupathi, S., Cosne, G., Juraver, A., Vardanyan, V., Hernández-García, A., et al., 2022 · 2022
Later among the works it cites.
Pairwise adversarial training for unsupervised class-imbalanced domain adaptation, in: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 1598–1606
Shi, W., Zhu, R., Li, S., 2022 · 2022
Later among the works it cites.
Safe self-refinement for transformer-based domain adaptation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7191–7200
Sun, T., Lu, C., Zhang, T., Ling, H., 2022 · 2022
Later among the works it cites.
Chain-of-thought prompting elicits reasoning in large language models, in: Advances in Neural Information Processing Systems
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E.H., Le, Q.V., Zhou, D., et al., 2022 · 2022
Later among the works it cites.
A review of high-throughput field phenotyping systems: Focusing on ground robots
Xu, R., Li, C., 2022b · 2022
Later among the works it cites.
Deep bidirectional language-knowledge graph pretraining
Yasunaga, M., Bosselut, A., Ren, H., Zhang, X., Manning, C.D., Liang, P.S., Leskovec, J., 2022 · 2022
Later among the works it cites.
A survey of knowledge-enhanced text generation
Yu, W., Zhu, C., Li, Z., Hu, Z., Wang, Q., Ji, H., Jiang, M., 2022 · 2022
Later among the works it cites.
Ammonia emissions, impacts, and mitigation strategies for poultry production: A critical review
Bist, R.B., Subedi, S., Chai, L., Yang, X., 2023 · 2023
Closest in time.
Sparks of artificial general intelligence: Early experiments with gpt-4
Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., et al., 2023 · 2023
Closest in time.
Poultry industry paradigms: connecting the dots
Castro, F., Chai, L., Arango, J., Owens, C., Smith, P., Reichelt, S., DuBois, C., Menconi, A., 2023 · 2023
Closest in time.
Chataug: Leveraging chatgpt for text data augmentation
Dai, H., Liu, Z., Liao, W., Huang, X., Wu, Z., Zhao, L., Liu, W., Liu, N., Li, S., Zhu, D., et al., 2023 · 2023
Closest in time.
Evaluating large language models on a highly-specialized topic, radiation oncology physics
Holmes, J., Liu, Z., Zhang, L., Ding, Y., Sio, T.T., McGee, L.A., Ashman, J.B., Li, X., Liu, T., Shen, J., et al., 2023 · 2023
Closest in time.
Language is not all you need: Aligning perception with language models
Huang, S., Dong, L., Wang, W., Hao, Y., Singhal, S., Ma, S., Lv, T., Cui, L., Mohammed, O.K., Liu, Q., et al., 2023 · 2023
Closest in time.
Understanding the potential applications of artificial intelligence in agriculture sector
Javaid, M., Haleem, A., Khan, I.H., Suman, R., 2023 · 2023
Closest in time.
Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.Y., Dollár, P., Girshick, R., 2023 · 2023
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