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This article introduces Bio-Eng-LMM AI chatbot, a versatile platform designed to enhance user interaction for educational and research purposes.
Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al., 2020 · 1901
Earlier work this paper cites.
Generalization through memorization: Nearest neighbor language models
Khandelwal, U., Levy, O., Jurafsky, D., Zettlemoyer, L., Lewis, M., 2019 · 1911
Earlier work this paper cites.
Learning internal representations by error propagation, parallel distributed processing, explorations in the microstructure of cognition, ed. de rumelhart and j. mcclelland. vol. 1. 1986
Rumelhart, D.E., Hinton, G.E., Williams, R.J., 1986 · 1986
Earlier work this paper cites.
Stochastic differential equations
Kloeden, P.E., Platen, E., Kloeden, P.E., Platen, E., 1992 · 1992
Earlier work this paper cites.
Long short-term memory
Hochreiter, S., Schmidhuber, J., 1997 · 1997
Earlier work this paper cites.
On relevance weights with little relevance information, in: SIGIR
Robertson, S.E., Walker, S., 1997 · 1997
Earlier work this paper cites.
The use of MMR, diversity-based reranking for reordering documents and producing summaries, in: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 335–336
Carbonell, J., Goldstein, J., 1998 · 1998
Earlier work this paper cites.
Industry evolution and competence development: the imperatives of technological convergence
Lei, D.T., 2000 · 2000
Earlier work this paper cites.
Document language models, query models, and risk minimization for information retrieval, in: SIGIR
Lafferty, J.D., Zhai, C., 2001 · 2001
Earlier work this paper cites.
Leveraging passage retrieval with generative models for open domain question answering
Izacard, G., Grave, E., 2020 · 2007
Earlier work this paper cites.
A survey of top-k query processing techniques in relational database systems
Ilyas, I.F., Beskales, G., Soliman, M.A., 2008 · 2008
Earlier work this paper cites.
The probabilistic relevance framework: BM25 and beyond
Robertson, S.E., Zaragoza, H., 2009 · 2009
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
DOSOVITSKIY, A., 2020 · 2010
Earlier work this paper cites.
Koizumi, Y., Ohishi, Y., Niizumi, D., Takeuchi, D., Yasuda, M., 2020 · 2012
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y., 2014 · 2014
Earlier work this paper cites.
Prezi versus powerpoint: The effects of varied digital presentation tools on students’ learning performance
Chou, P.N., Chang, C.C., Lu, P.F., 2015 · 2015
Earlier work this paper cites.
Learning maximal marginal relevance model via directly optimizing diversity evaluation measures, in: Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval, pp. 113–122
Xia, L., Xu, J., Lan, Y., Guo, J., Cheng, X., 2015 · 2015
Earlier work this paper cites.
Academic presenter: A new storytelling presentation software for academic purposes
Avsar, B., Aliabadi, D.E., Aliabadi, E.E., Yousefnezhad, R., 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I., 2017 · 2017
Earlier work this paper cites.
Generative adversarial networks
Goodfellow, I., Pouget-Abadie, J., Mirza, M., et al., 2020 · 2020
Earlier work this paper cites.
Retrieval augmented language model pre-training, in: International conference on machine learning, PMLR. pp. 3929–3938
Guu, K., Lee, K., Tung, Z., Pasupat, P., Chang, M., 2020 · 2020
Earlier work this paper cites.
A review on the long short-term memory model
Houdt, G.V., et al., 2020 · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.t., Rocktäschel, T., et al., 2020 · 2020
Earlier work this paper cites.
Catastrophic forgetting and mode collapse in GANs, in: 2020 international joint conference on neural networks (ijcnn), IEEE. pp. 1–10
Thanh-Tung, H., Tran, T., 2020 · 2020
Earlier work this paper cites.
Retrievegan: Image synthesis via differentiable patch retrieval, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part VIII 16, Springer. pp. 242–257
Tseng, H.Y., Lee, H.Y., Jiang, L., Yang, M.H., Yang, W., 2020 · 2020
Earlier work this paper cites.
A systematic review of educational digital storytelling
Wu, J., Chen, D.T.V., 2020 · 2020
Earlier work this paper cites.
Unified pre-training for program understanding and generation
Ahmad, W.U., Chakraborty, S., Ray, B., Chang, K.W., 2021 · 2021
Earlier work this paper cites.
Case-based reasoning for natural language queries over knowledge bases, in: EMNLP
Das, R., Zaheer, M., Thai, D., et al., 2021 · 2021
Earlier work this paper cites.
Graphcodebert: Pre-training code representations with data flow, in: ICLR
Guo, D., Ren, S., et al., 2021 · 2021
Earlier work this paper cites.
Efficient nearest neighbor language models
He, J., Neubig, G., Berg-Kirkpatrick, T., 2021 · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., Chen, W., 2021 · 2021
Cited alongside, same era.
Unseen entity handling in complex question answering over knowledge base via language generation, in: EMNLP Findings
Huang, X., Kim, J., Zou, B., 2021 · 2021
Cited alongside, same era.
Retrieval augmented code generation and summarization
Parvez, M.R., Ahmad, W.U., Chakraborty, S., Ray, B., Chang, K.W., 2021 · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision, in: ICML
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I., 2021 · 2021
Cited alongside, same era.
Smallcap: lightweight image captioning prompted with retrieval augmentation, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2840–2849
Ramos, R., Martins, B., Elliott, D., Kementchedjhieva, Y., 2023 · 2023
Later among the works it cites.
Efficient transformers: A survey
Tay, Y., Dehghani, M., Bahri, D., Metzler, D., 2023 · 2023
Later among the works it cites.
Llama: Open and efficient foundation language models
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al., 2023 · 2023
Later among the works it cites.
Multimodal large language models: A survey, in: 2023 IEEE International Conference on Big Data (BigData), IEEE. pp. 2247–2256
Wu, J., Gan, W., Chen, Z., Wan, S., Philip, S.Y., 2023b · 2023
Later among the works it cites.
mplug-owl: Modularization empowers large language models with multimodality
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Yan, W., Zhang, Y., Abbeel, P., Srinivas, A., 2021 · 2021
Cited alongside, same era.
stable-diffusion-3-medium
AI, S., 2022 · 2022
Cited alongside, same era.
Improving language models by retrieving from trillions of tokens, in: International conference on machine learning, PMLR. pp. 2206–2240
Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., Van Den Driessche, G.B., Lespiau, J.B., Damoc, B., Clark, A., et al., 2022 · 2022
Cited alongside, same era.
Visualgpt: Data-efficient adaptation of pretrained language models for image captioning, in: CVPR
Chen, J., Guo, H., Yi, K., et al., 2022 · 2022
Cited alongside, same era.
Logical form generation via multi-task learning for complex question answering over knowledge bases, in: Proceedings of the 29th International Conference on Computational Linguistics, pp. 1687–1696
Hu, X., Wu, X., Shu, Y., Qu, Y., 2022 · 2022
Cited alongside, same era.
Elucidating the design space of diffusion-based generative models
Karras, T., Aittala, M., Aila, T., Laine, S., 2022 · 2022
Cited alongside, same era.
Foundations and trends in multimodal machine learning: Principles, challenges, and open questions
Liang, P.P., Zadeh, A., Morency, L.P., 2022 · 2022
Cited alongside, same era.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Lu, P., Mishra, S., Xia, T., Qiu, L., Chang, K.W., Zhu, S.C., Tafjord, O., Clark, P., Kalyan, A., 2022 · 2022
Cited alongside, same era.
Ye, Q., Xu, H., Xu, G., Ye, J., Yan, M., Zhou, Y., Wang, J., Hu, A., Shi, P., Shi, Y., et al., 2023 · 2023
Later among the works it cites.
From text to video with ai: the rise and potential of sora in education and libraries
Adetayo, A.J., Enamudu, A.I., Lawal, F.M., Odunewu, A.O., 2024 · 2024
Closest in time.
Knowledge retrieval and diagnostics in cloud services with large language models
Baghdasaryan, A., Bunarjyan, T., Poghosyan, A., Harutyunyan, A., El-Zein, J., 2024 · 2024
Closest in time.
A survey of multimodal large language model from a data-centric perspective
Bai, T., Liang, H., Wan, B., Yang, L., Li, B., Wang, Y., Cui, B., He, C., Yuan, B., Zhang, W., 2024 · 2024
Closest in time.
Can Generative AI improve social science?
Bail, C.A., 2024 · 2024
Closest in time.
Teaching highly intelligent primary school kids energy system complexity
Chappin, E., 2023 · 2024
Closest in time.
Impact of ai assistance on student agency
Darvishi, A., Khosravi, H., Sadiq, S., Gašević, D., Siemens, G., 2024 · 2024
Closest in time.
What makes quantization for large language model hard? an empirical study from the lens of perturbation, in: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 18082–18089
Gong, Z., Liu, J., Wang, J., Cai, X., Zhao, D., Yan, R., 2024 · 2024
Closest in time.
Genegpt: Augmenting large language models with domain tools for improved access to biomedical information
Jin, Q., Yang, Y., Chen, Q., Lu, Z., 2024 · 2024
Closest in time.
Advancing multimodal diagnostics: Integrating industrial textual data and domain knowledge with large language models
Jose, S., Nguyen, K.T., Medjaher, K., Zemouri, R., Lévesque, M., Tahan, A., 2024 · 2024
Closest in time.
From deep neural language models to LLMs, in: Large Language Models in Cybersecurity: Threats, Exposure and Mitigation. Springer, pp. 3–17
Kucharavy, A., 2024 · 2024
Closest in time.
On the generalization properties of diffusion models
Li, P., Li, Z., Zhang, H., Bian, J., 2024 · 2024
Closest in time.
Llava-next: Improved reasoning, ocr, and world knowledge
Liu, H., Li, C., Li, Y., Li, B., Zhang, Y., Shen, S., Lee, Y.J., 2024a · 2024
Closest in time.
Google deepmind’s gemini ai versus chatgpt: A comparative analysis in ophthalmology
Masalkhi, M., Ong, J., Waisberg, E., Lee, A.G., 2024 · 2024
Closest in time.
Turkishbertweet: Fast and reliable large language model for social media analysis
Najafi, A., Varol, O., 2024 · 2024
Closest in time.
Language model-guided student performance prediction with multimodal auxiliary information
Oh, C., Park, M., Lim, S., Song, K., 2024 · 2024
Closest in time.
When quantization affects confidence of large language models?
Proskurina, I., Brun, L., Metzler, G., Velcin, J., 2024 · 2024
Closest in time.
Retrieval-augmented score distillation for text-to-3d generation
Seo, J., Hong, S., Jang, W., Kim, I.H., Kwak, M., Lee, D., Kim, S., 2024 · 2024
Closest in time.
Chatgpt improves creative problem-solving performance in university students: An experimental study
Urban, M., Děchtěrenko, F., Lukavskỳ, J., Hrabalová, V., Svacha, F., Brom, C., Urban, K., 2024 · 2024
Closest in time.
Potential for gpt technology to optimize future clinical decision-making using retrieval-augmented generation
Wang, C., Ong, J., Wang, C., Ong, H., Cheng, R., Ong, D., 2024 · 2024
Closest in time.
When ai eats itself: On the caveats of data pollution in the era of generative ai
Xing, X., Shi, F., Huang, J., Wu, Y., Nan, Y., Zhang, S., Fang, Y., Roberts, M., Schönlieb, C.B., Del Ser, J., et al., 2024 · 2024
Closest in time.
Evaluation of retrieval-augmented generation: A survey
Yu, H., Gan, A., Zhang, K., Tong, S., Liu, Q., Liu, Z., 2024 · 2024
Closest in time.
Retrieval-augmented generation for ai-generated content: A survey
Zhao, P., Zhang, H., Yu, Q., Wang, Z., Geng, Y., Fu, F., Yang, L., Zhang, W., Cui, B., 2024 · 2024
Closest in time.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Zhu, D., Chen, J., Shen, X., Li, X., Elhoseiny, M., 2023 · 2024
Closest in time.
The European Energy Vision 2060 (EU EnVis-2060): Scenario Parametrization
Löffler, K., Moskalenko, N., Herpich, P., Hanto, J., Hainsch, K., Bornemann, J., Diesing, A., Dupke, R., Barani, M., 2024 · 2060
Closest in time.