在训练数据中加入质量不高的数据会剧烈地降低模型的知识容量,甚至可能导致模型知识容量缩减到原来的1/20。即使通过增加训练时间和数据量能有所改善,效果仍然明显不如从前,可能只恢复到原来的1/3。然而,这里有个免费的午餐:只需在每条数据前添加数据的来源标签/领域标签,就可以恢复模型的知识容量。这种...
Physics of Language Models, Part 3, Knowledgemp.weixin.qq.com/s/ZdNZxOajTyHH6PuwSB5HFA?token=1364753235 =zh_CN lumosity:LLM: Physics of Language Models, part 2, Grade-School Math2 赞同 · 0 评论文章 Physics of Language Models, Part 3, Knowledge Part 3.1, Knowledge Storage and Extract...
[LG] Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process O网页链接 通过可控合成小学数学问题数据集以及模型输出和探测分析,原理性地研究了语言模型如何获得解决这类问题的推理技能,发现了它学会人类相关技能和超越人类推理技能的证据,并指出模型深度对推理长度至关重要。 ...
Language models have demonstrated remarkable performance in solving reasoning tasks; however, even the strongest models still occasionally make reasoning mistakes. Recently, there has been active research aimed at improving reasoning accuracy, particularly by using pretrained language models to "self-correct...
Rapid advances in the capabilities of large language models and the broad accessibility of tools powered by this technology have led to both excitement and concern regarding their use in science. Four experts in artificial intelligence ethics and policy
The Physics of Atmospheres (Cambridge Univ. Press, 2002). Hasselmann, K. Stochastic climate models. Part I. Theory. Tellus 28, 473–485 (1976). Article ADS Google Scholar Clement, A. K. et al. The Atlantic Multidecadal Oscillation without a role for ocean circulation. Science 350, 320–...
The following guidance refers only to the writing process, and not to the use of AI tools to analyse and draw insights from data as part of the research process: Generative AI and AI-assisted technologies should only be used in the writing process to improve the readability and language of ...
This study used structural topic models (STMs) to analyze physics pre-service teachers’ conceptual understanding of scientific literacy. Participants
语言模型物理学:第 3.3 部分,知识容量缩放定律 Physics of Language Models: Part 3.3,Knowledge Capacity Scaling Laws 作者信息: Zeyuan Allen-Zhu zeyuanallenzhu@meta.com Meta / FAIR Labs Yuanzhi Li Yuanzhi.Li@mbzuai.ac.ae Mohamed bin Zayed University of AI...
Bert: Pre-training of deep bidirectional transformers for language understanding. Preprint at arXiv 1810.04805 (2018). Brown, T. B. et al. Language models are few-shot learners. Preprint at arXiv 2005.14165 (2020). Hamilton, W. L., Ying, R. & Leskovec, J. in Proc. 31st International ...