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Leveraging Natural Supervision: Appendix A - Appendix to Chapter 3
Manage episode 421620364 series 3474148
This story was originally published on HackerNoon at: https://hackernoon.com/leveraging-natural-supervision-appendix-a-appendix-to-chapter-3.
In this study, researchers describe three lines of work that seek to improve the training and evaluation of neural models using naturally-occurring supervision.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llm-natural-supervision, #llm-self-supervision, #llm-language-pretraining, #llm-word-prediction, #ai-language-modeling, #ai-vector-representations, #ai-neural-models, #ai-sentence-representations, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
In this study, researchers describe three lines of work that seek to improve the training and evaluation of neural models using naturally-occurring supervision.
472 episodios
Manage episode 421620364 series 3474148
This story was originally published on HackerNoon at: https://hackernoon.com/leveraging-natural-supervision-appendix-a-appendix-to-chapter-3.
In this study, researchers describe three lines of work that seek to improve the training and evaluation of neural models using naturally-occurring supervision.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #llm-natural-supervision, #llm-self-supervision, #llm-language-pretraining, #llm-word-prediction, #ai-language-modeling, #ai-vector-representations, #ai-neural-models, #ai-sentence-representations, and more.
This story was written by: @textmodels. Learn more about this writer by checking @textmodels's about page, and for more stories, please visit hackernoon.com.
In this study, researchers describe three lines of work that seek to improve the training and evaluation of neural models using naturally-occurring supervision.
472 episodios
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