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The rapid growth of research in Pattern Analysis and Machine Intelligence (PAMI) has rendered literature reviews essential for consolidating and interpreting knowledge across its many subfields.
Merton, R.K.: The matthew effect in science: The reward and communication systems of science are considered. Science 159
1968
Earlier work this paper cites.
Small, H.: Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for information Science 24
1973
Earlier work this paper cites.
Broadus, R.N.: Toward a definition of “bibliometrics”. Scientometrics 12
1987
Earlier work this paper cites.
Matricciani, E.: The probability distribution of the age of references in engineering papers. IEEE Transactions on Professional Communication 34
1991
Earlier work this paper cites.
Egghe, L., et al.: Citation age data and the obsolescence function: Fits and explanations. Information Processing & Management 28
1992
Earlier work this paper cites.
Kostoff, R.N., Hartley, J.: Open letter to technical journal editors regarding structured abstracts: this letter proposes that structured abstracts be required for all technical journal articles. Journal of Information Science 28
2002
Earlier work this paper cites.
Moed, H.F.: Statistical relationships between downloads and citations at the level of individual documents within a single journal. Journal of the American Society for Information Science and Technology 56
2005
Earlier work this paper cites.
Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvisticae Investigationes 30
2007
Earlier work this paper cites.
Tatsioni, A., Bonitsis, N.G., Ioannidis, J.P.A.: Persistence of contradicted claims in the literature. JAMA 298 21
2007
Earlier work this paper cites.
Yujian, L., Bo, L.: A normalized levenshtein distance metric. IEEE transactions on pattern analysis and machine intelligence 29
2007
Earlier work this paper cites.
Beel, J., Gipp, B.: Google scholar’s ranking algorithm: an introductory overview. In: Proceedings of the 12th international conference on scientometrics and informetrics (ISSI’09). vol. 1, pp. 230–241. Rio de Janeiro (Brazil) (2009)
2009
Earlier work this paper cites.
Grant, M.J., Booth, A.: A typology of reviews: an analysis of 14 review types and associated methodologies. Health information & libraries journal 26
2009
Earlier work this paper cites.
Beel, J., Gipp, B.: Academic search engine spam and google scholar’s resilience against it. Journal of electronic publishing 13
2010
Earlier work this paper cites.
Beel, J., Gipp, B.: On the robustness of google scholar against spam. In: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia. pp. 297–298 (2010)
2010
Earlier work this paper cites.
Kitchenham, B., Pretorius, R., Budgen, D., Brereton, O.P., Turner, M., Niazi, M., Linkman, S.: Systematic literature reviews in software engineering–a tertiary study. Information and software technology 52
2010
Earlier work this paper cites.
Moed, H.F.: Measuring contextual citation impact of scientific journals. Journal of informetrics 4
2010
Earlier work this paper cites.
for Cell Biology, A.S., et al.: San francisco declaration on research assessment (dora) (2012)
2012
Earlier work this paper cites.
Beller, E.M., Glasziou, P.P., Altman, D.G., Hopewell, S., Bastian, H., Chalmers, I., Gøtzsche, P.C., Lasserson, T., Tovey, D., for Abstracts Group, P.: Prisma for abstracts: reporting systematic reviews in journal and conference abstracts. PLoS medicine 10
2013
Earlier work this paper cites.
Sariyanidi, E., Gunes, H., Cavallaro, A.: Automatic analysis of facial affect: A survey of registration, representation, and recognition. IEEE transactions on pattern analysis and machine intelligence 37
2014
Earlier work this paper cites.
Brzezinski, M.: Power laws in citation distributions: evidence from scopus. Scientometrics 103
2015
Earlier work this paper cites.
Hicks, D., Wouters, P., Waltman, L., De Rijcke, S., Rafols, I.: Bibliometrics: the leiden manifesto for research metrics. Nature 520
2015
Earlier work this paper cites.
Trueger, N.S., Thoma, B., Hsu, C.H., Sullivan, D., Peters, L., Lin, M.: The altmetric score: a new measure for article-level dissemination and impact. Annals of emergency medicine 66
2015
Earlier work this paper cites.
Bruce, R.C.: Application of the gompertz function in studies of growth in dusky salamanders (plethodontidae: Desmognathus). Copeia 104
2016
Earlier work this paper cites.
Hutchins, B.I., Yuan, X., Anderson, J.M., Santangelo, G.M.: Relative citation ratio (rcr): a new metric that uses citation rates to measure influence at the article level. PLoS biology 14
2016
Earlier work this paper cites.
Litjens, G., Kooi, T., Bejnordi, B.E., Setio, A.A.A., Ciompi, F., Ghafoorian, M., Van Der Laak, J.A., Van Ginneken, B., Sánchez, C.I.: A survey on deep learning in medical image analysis. Medical image analysis 42
2017
Earlier work this paper cites.
Nahid, A.A., Kong, Y.: Involvement of machine learning for breast cancer image classification: a survey. Computational and mathematical methods in medicine 2017
2017
Earlier work this paper cites.
Rawat, W., Wang, Z.: Deep convolutional neural networks for image classification: A comprehensive review. Neural computation 29
2017
Earlier work this paper cites.
Brysbaert, M.: How many words do we read per minute? a review and meta-analysis of reading rate. Journal of memory and language 109
2019
Earlier work this paper cites.
Purkayastha, A., Palmaro, E., Falk-Krzesinski, H.J., Baas, J.: Comparison of two article-level, field-independent citation metrics: Field-weighted citation impact (fwci) and relative citation ratio (rcr). Journal of Informetrics 13
2019
Earlier work this paper cites.
Weegar, R., Pérez, A., Casillas, A., Oronoz, M.: Recent advances in swedish and spanish medical entity recognition in clinical texts using deep neural approaches. BMC medical informatics and decision making 19
2019
Earlier work this paper cites.
Yu, Y., Si, X., Hu, C., Zhang, J.: A review of recurrent neural networks: Lstm cells and network architectures. Neural computation 31
2019
Earlier work this paper cites.
Yue, L., Chen, W., Li, X., Zuo, W., Yin, M.: A survey of sentiment analysis in social media. Knowledge and Information Systems 60
2019
Earlier work this paper cites.
Zhang, H., Hong, X.: Recent progresses on object detection: a brief review. Multimedia Tools and Applications 78
2019
Earlier work this paper cites.
Zhao, Z.Q., Zheng, P., Xu, S.t., Wu, X.: Object detection with deep learning: A review. IEEE transactions on neural networks and learning systems 30
2019
Earlier work this paper cites.
Al-Moslmi, T., Ocaña, M.G., Opdahl, A.L., Veres, C.: Named entity extraction for knowledge graphs: A literature overview. IEEE Access 8
2020
Earlier work this paper cites.
Bandini, A., Zariffa, J.: Analysis of the hands in egocentric vision: A survey. IEEE transactions on pattern analysis and machine intelligence (2020)
2020
Earlier work this paper cites.
Cao, Y., Geddes, T.A., Yang, J.Y.H., Yang, P.: Ensemble deep learning in bioinformatics. Nature Machine Intelligence 2
2020
Earlier work this paper cites.
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al.: An image is worth 16x16 words: Transformers for image recognition at scale. In: International Conference on Learning Representations (2020)
2020
Earlier work this paper cites.
Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., Bennamoun, M.: Deep learning for 3d point clouds: A survey. IEEE transactions on pattern analysis and machine intelligence 43
2020
Earlier work this paper cites.
Hao, S., Zhou, Y., Guo, Y.: A brief survey on semantic segmentation with deep learning. Neurocomputing 406
2020
Earlier work this paper cites.
Li, J., Sun, A., Han, J., Li, C.: A survey on deep learning for named entity recognition. IEEE Transactions on Knowledge and Data Engineering 34
2020
Earlier work this paper cites.
Li, K., Wan, G., Cheng, G., Meng, L., Han, J.: Object detection in optical remote sensing images: A survey and a new benchmark. ISPRS journal of photogrammetry and remote sensing 159
2020
Earlier work this paper cites.
Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., Pietikäinen, M.: Deep learning for generic object detection: A survey. International journal of computer vision 128
2020
Earlier work this paper cites.
Memon, J., Sami, M., Khan, R.A., Uddin, M.: Handwritten optical character recognition (ocr): A comprehensive systematic literature review (slr). IEEE access 8
2020
Earlier work this paper cites.
Shen, Z., Tong, S., Chen, F., Yang, L.: The utilization of paper-level classification system on the evaluation of journal impact. arXiv e-prints pp. arXiv–2006 (2020)
2020
Earlier work this paper cites.
Teixeira da Silva, J.A.: Citescore: Advances, evolution, applications, and limitations. Publishing Research Quarterly 36
2020
Earlier work this paper cites.
Vaghi, C., Rodallec, A., Fanciullino, R., Ciccolini, J., Mochel, J.P., Mastri, M., Poignard, C., Ebos, J.M., Benzekry, S.: Population modeling of tumor growth curves and the reduced gompertz model improve prediction of the age of experimental tumors. PLoS computational biology 16
2020
Earlier work this paper cites.
Xiao, Y., Tian, Z., Yu, J., Zhang, Y., Liu, S., Du, S., Lan, X.: A review of object detection based on deep learning. Multimedia Tools and Applications 79
2020
Earlier work this paper cites.
Yadav, A., Vishwakarma, D.K.: Sentiment analysis using deep learning architectures: a review. Artificial Intelligence Review 53
2020
Earlier work this paper cites.
Alzahrani, Y., Boufama, B.: Biomedical image segmentation: a survey. SN Computer Science 2
2021
Earlier work this paper cites.
Atz, K., Grisoni, F., Schneider, G.: Geometric deep learning on molecular representations. Nature Machine Intelligence 3
2021
Earlier work this paper cites.
Chandra, M.A., Bedi, S.: Survey on svm and their application in image classification. International Journal of Information Technology 13
2021
Earlier work this paper cites.
Chen, L., Li, S., Bai, Q., Yang, J., Jiang, S., Miao, Y.: Review of image classification algorithms based on convolutional neural networks. Remote Sensing 13
2021
Earlier work this paper cites.
Hussain, T., Muhammad, K., Ding, W., Lloret, J., Baik, S.W., de Albuquerque, V.H.C.: A comprehensive survey of multi-view video summarization. Pattern Recognition 109
2021
Earlier work this paper cites.
Li, Z., Liu, F., Yang, W., Peng, S., Zhou, J.: A survey of convolutional neural networks: analysis, applications, and prospects. IEEE transactions on neural networks and learning systems (2021)
2021
Cited alongside, same era.
Lim, B., Zohren, S.: Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A 379
2021
Cited alongside, same era.
Liu, X., Song, L., Liu, S., Zhang, Y.: A review of deep-learning-based medical image segmentation methods. Sustainability 13
2021
Cited alongside, same era.
Liu, X., Zhang, F., Hou, Z., Mian, L., Wang, Z., Zhang, J., Tang, J.: Self-supervised learning: Generative or contrastive. IEEE transactions on knowledge and data engineering 35
2021
Cited alongside, same era.
Ma, J., Chen, J., Ng, M., Huang, R., Li, Y., Li, C., Yang, X., Martel, A.L.: Loss odyssey in medical image segmentation. Medical Image Analysis 71
2023
Later among the works it cites.
Liu, T., Zhang, L., Wang, Y., Guan, J., Fu, Y., Zhao, J., Zhou, S.: Recent few-shot object detection algorithms: A survey with performance comparison. ACM Transactions on Intelligent Systems and Technology 14
2023
Later among the works it cites.
Liu, Y., Zhang, Y., Wang, Y., Hou, F., Yuan, J., Tian, J., Zhang, Y., Shi, Z., Fan, J., He, Z.: A survey of visual transformers. IEEE Transactions on Neural Networks and Learning Systems (2023)
2023
Later among the works it cites.
Lu, J., Gong, P., Ye, J., Zhang, J., Zhang, C.: A survey on machine learning from few samples. Pattern Recognition 139
2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2021
Cited alongside, same era.
Machado, G.R., Silva, E., Goldschmidt, R.R.: Adversarial machine learning in image classification: A survey toward the defender’s perspective. ACM Computing Surveys (CSUR) 55
2021
Cited alongside, same era.
Malik, M., Malik, M.K., Mehmood, K., Makhdoom, I.: Automatic speech recognition: a survey. Multimedia Tools and Applications 80
2021
Cited alongside, same era.
Martín-Martín, A., Thelwall, M., Orduna-Malea, E., Delgado López-Cózar, E.: Google scholar, microsoft academic, scopus, dimensions, web of science, and opencitations’ coci: a multidisciplinary comparison of coverage via citations. Scientometrics 126
2021
Cited alongside, same era.
Min, B., Ross, H., Sulem, E., Veyseh, A.P.B., Nguyen, T.H., Sainz, O., Agirre, E., Heintz, I., Roth, D.: Recent advances in natural language processing via large pre-trained language models: A survey. ACM Computing Surveys (2021)
2021
Cited alongside, same era.
Minaee, S., Boykov, Y., Porikli, F., Plaza, A., Kehtarnavaz, N., Terzopoulos, D.: Image segmentation using deep learning: A survey. IEEE transactions on pattern analysis and machine intelligence 44
2021
Cited alongside, same era.
Nasar, Z., Jaffry, S.W., Malik, M.K.: Named entity recognition and relation extraction: State-of-the-art. ACM Computing Surveys (CSUR) 54
2021
Cited alongside, same era.
Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A., Brennan, S.E., et al.: The prisma 2020 statement: an updated guideline for reporting systematic reviews. bmj 372
2021
Cited alongside, same era.
Maslej, N., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., Ngo, H., Niebles, J.C., Parli, V., Shoham, Y., Wald, R., Clark, J., Perrault, R.: The ai index 2023 annual report. Tech. rep., AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA (April 2023)
2023
Later among the works it cites.
Mazurowski, M.A., Dong, H., Gu, H., Yang, J., Konz, N., Zhang, Y.: Segment anything model for medical image analysis: an experimental study. Medical Image Analysis 89
2023
Later among the works it cites.
OpenAI: Chatgpt: optimizing language models for dialogue. https://openai.com/blog/chatgpt/ (2022), accessed 25 December 2023
2023
Later among the works it cites.
2023
Later among the works it cites.
Paper Digest: Paper digest ai-powered research platform. https://www.paperdigest.org/review/ (2023), accessed 25 December 2023
2023
Later among the works it cites.
PDFMiner: PDFMiner.six, https://github.com/pdfminer/pdfminer.six , [Online; accessed 14-Nov-2023]
2023
Later among the works it cites.
Prabhavalkar, R., Hori, T., Sainath, T.N., Schlüter, R., Watanabe, S.: End-to-end speech recognition: A survey. IEEE/ACM Transactions on Audio, Speech, and Language Processing (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Qureshi, I., Yan, J., Abbas, Q., Shaheed, K., Riaz, A.B., Wahid, A., Khan, M.W.J., Szczuko, P.: Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends. Information Fusion 90
2023
Later among the works it cites.
Seamlees: Seamless - ai literature review tool for scientific research. https://seaml.es/ (2023), accessed 25 December 2023
2023
Later among the works it cites.
Shen, W., Peng, Z., Wang, X., Wang, H., Cen, J., Jiang, D., Xie, L., Yang, X., Tian, Q.: A survey on label-efficient deep image segmentation: Bridging the gap between weak supervision and dense prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)
2023
Later among the works it cites.
Tong, S., Chen, F., Yang, L., Shen, Z.: Novel utilization of a paper-level classification system for the evaluation of journal impact: An update of the cas journal ranking. Quantitative Science Studies pp. 1–16 (2023)
2023
Later among the works it cites.
de la Torre-López, J., Ramírez, A., Romero, J.R.: Artificial intelligence to automate the systematic review of scientific literature. Computing 105
2023
Later among the works it cites.
2023
Later among the works it cites.
Wang, J., Liu, Z., Zhao, L., Wu, Z., Ma, C., Yu, S., Dai, H., Yang, Q., Liu, Y., Zhang, S., et al.: Review of large vision models and visual prompt engineering. Meta-Radiology p. 100047 (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Wu, J., Gan, W., Chen, Z., Wan, S., Philip, S.Y.: Multimodal large language models: A survey. In: 2023 IEEE International Conference on Big Data (BigData). pp. 2247–2256. IEEE (2023)
2023
Later among the works it cites.
Xing, Z., Feng, Q., Chen, H., Dai, Q., Hu, H., Xu, H., Wu, Z., Jiang, Y.G.: A survey on video diffusion models. ACM Computing Surveys (2023)
2023
Later among the works it cites.
Yang, L., Zhang, Z., Song, Y., Hong, S., Xu, R., Zhao, Y., Zhang, W., Cui, B., Yang, M.H.: Diffusion models: A comprehensive survey of methods and applications. ACM Computing Surveys 56
2023
Later among the works it cites.
2023
Later among the works it cites.
Yu, J., Yin, H., Xia, X., Chen, T., Li, J., Huang, Z.: Self-supervised learning for recommender systems: A survey. IEEE Transactions on Knowledge and Data Engineering (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
Zybaczynska, J., Norris, M., Modi, S., Brennan, J., Jhaveri, P., Craig, T.J., Al-Shaikhly, T.: Artificial intelligence-generated scientific literature-a critical appraisal. The Journal of Allergy and Clinical Immunology: In Practice (2023)
2023
Later among the works it cites.
Cheng, G., Huang, Y., Li, X., Lyu, S., Xu, Z., Zhao, H., Zhao, Q., Xiang, S.: Change detection methods for remote sensing in the last decade: A comprehensive review. Remote Sensing 16
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
Lai, Y., Wu, Y., Wang, Y., Hu, W., Zheng, C.: Instruct large language models to generate scientific literature survey step by step. In: CCF International Conference on Natural Language Processing and Chinese Computing. pp. 484–496. Springer (2024)
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
Tian, Y., Gu, X., Li, A., Zhang, H., Xu, R., Li, Y., Liu, M.: Overview of the nlpcc2024 shared task 6: Scientific literature survey generation. In: CCF International Conference on Natural Language Processing and Chinese Computing. pp. 400–408. Springer (2024)
2024
Closest in time.
Wang, Y., Guo, Q., Yao, W., Zhang, H., Zhang, X., Wu, Z., Zhang, M., Dai, X., Zhang, M., Wen, Q., Ye, W., Zhang, S., Zhang, Y.: Autosurvey: Large language models can automatically write surveys. In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024)
2024
Closest in time.
de Winter, J.: Can chatgpt be used to predict citation counts, readership, and social media interaction? an exploration among 2222 scientific abstracts. Scientometrics 129
2024
Closest in time.
2024
Closest in time.
Zhang, H., Zhu, Y., Wang, D., Zhang, L., Chen, T., Wang, Z., Ye, Z.: A survey on visual mamba. Applied Sciences 14
2024
Closest in time.
Zhou, D.W., Wang, Q.W., Qi, Z.H., Ye, H.J., Zhan, D.C., Liu, Z.: Class-incremental learning: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)
2024
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
2025
Closest in time.
Zhao, P., Xing, Q., Dou, K., Tian, J., Tai, Y., Yang, J., Cheng, M.M., Li, X.: From words to worth: Newborn article impact prediction with llm. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 39, pp. 1183–1191 (2025)
2025
Closest in time.