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Sparse Mixtures of Experts (SMoE) scales model capacity without significant increases in training and inference costs, but exhibits the following two issues: (1) Low expert activation, where only a small subset of experts are activated for optimization.
Roberta: A robustly optimized BERT pretraining approach
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V · 1907
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Im2text: Describing images using 1 million captioned photographs
Ordonez, V., Kulkarni, G., and Berg, T. L · 2011
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Kudo, T. and Richardson, J · 2012
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Microsoft COCO: common objects in context
Lin, T., Maire, M., Belongie, S. J., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., and Fidler, S · 2015
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Making the V in VQA matter: Elevating the role of image understanding in visual question answering
Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., and Parikh, D · 2017
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L., Shamma, D. A., Bernstein, M. S., and Fei-Fei, L · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2017
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XNLI: Evaluating cross-lingual sentence representations
Conneau, A., Rinott, R., Lample, G., Williams, A., Bowman, S., Schwenk, H., and Stoyanov, V · 2018
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Improving language understanding by generative pre-training
Radford, A., Narasimhan, K., Salimans, T., and Sutskever, I · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Sharma, P., Ding, N., Goodman, S., and Soricut, R · 2018
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A simple method for commonsense reasoning
Trinh, T. H. and Le, Q. V · 2018
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Cross-lingual language model pretraining, 2019
Lample, G. and Conneau, A · 2019
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A corpus for reasoning about natural language grounded in photographs
Suhr, A., Zhou, S., Zhang, A., Zhang, I., Bai, H., and Artzi, Y · 2019
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UniLMv2: Pseudo-masked language models for unified language model pre-training
Bao, H., Dong, L., Wei, F., Wang, W., Yang, N., Liu, X., Wang, Y., Gao, J., Piao, S., Zhou, M., and Hon, H · 2020
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Unsupervised cross-lingual representation learning at scale
Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., and Stoyanov, V · 2020
Cited alongside, same era.
Gshard: Scaling giant models with conditional computation and automatic sharding
Lepikhin, D., Lee, H., Xu, Y., Chen, D., Firat, O., Huang, Y., Krikun, M., Shazeer, N., and Chen, Z · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2020
Cited alongside, same era.
Unified scaling laws for routed language models
Clark, A., Casas, D. d. l., Guy, A., Mensch, A., Paganini, M., Hoffmann, J., Damoc, B., Hechtman, B., Cai, T., Borgeaud, S., et al · 2022
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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
Fedus, W., Zoph, B., and Shazeer, N · 2022
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Image as a foreign language: Beit pretraining for all vision and vision-language tasks
Wang, W., Bao, H., Dong, L., Bjorck, J., Peng, Z., Liu, Q., Aggarwal, K., Mohammed, O. K., Singhal, S., Som, S., et al · 2022
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Redpajama: An open source recipe to reproduce llama training dataset, 2023
Computer, T · 2023
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A framework for few-shot language model evaluation, 12 2023
Gao, L., Tow, J., Abbasi, B., Biderman, S., Black, S., DiPofi, A., Foster, C., Golding, L., Hsu, J., Le Noac’h, A., Li, H., McDonell, K., Muennighoff, N., Ociepa, C., Phang, J., Reynolds, L., Schoelkopf, H., Skowron, A., Sutawika, L., Tang, E., Thite, A., Wang, B., Wang, K., and Zou, A · 2023
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Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Changpinyo, S., Sharma, P., Ding, N., and Soricut, R · 2021
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Glam: Efficient scaling of language models with mixture-of-experts
Du, N., Huang, Y., Dai, A. M., Tong, S., Lepikhin, D., Xu, Y., Krikun, M., Zhou, Y., Yu, A. W., Firat, O., et al · 2021
Cited alongside, same era.
Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
Kumatani, K., Gmyr, R., Salinas, F. C., Liu, L., Zuo, W., Patel, D., Sun, E., and Shi, Y · 2021
Cited alongside, same era.
{GS}hard: Scaling giant models with conditional computation and automatic sharding
Lepikhin, D., Lee, H., Xu, Y., Chen, D., Firat, O., Huang, Y., Krikun, M., Shazeer, N., and Chen, Z · 2021
Cited alongside, same era.
M6-t: Exploring sparse expert models and beyond
Yang, A., Lin, J., Men, R., Zhou, C., Jiang, L., Jia, X., Wang, A., Zhang, J., Wang, J., Li, Y., et al · 2021
Cited alongside, same era.
On the representation collapse of sparse mixture of experts
Chi, Z., Dong, L., Huang, S., Dai, D., Ma, S., Patra, B., Singhal, S., Bajaj, P., Song, X., Mao, X.-L., et al · 2022
Cited alongside, same era.
Scaling instruction-finetuned language models
Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al · 2022
Cited alongside, same era.
Later among the works it cites.
OpenAI · 2023
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Kosmos-2: Grounding multimodal large language models to the world
Peng, Z., Wang, W., Dong, L., Hao, Y., Huang, S., Ma, S., and Wei, F · 2023
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Task-based moe for multitask multilingual machine translation
Pham, H., Kim, Y. J., Mukherjee, S., Woodruff, D. P., Poczos, B., and Awadalla, H. H · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al · 2023
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Moec: Mixture of expert clusters
Xie, Y., Huang, S., Chen, T., and Wei, F · 2023
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Sparse moe with language guided routing for multilingual machine translation
Zhao, X., Chen, X., Cheng, Y., and Chen, T · 2023
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Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., Casas, D. d. l., Hanna, E. B., Bressand, F., et al · 2024
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