Explore and analyze the Top Large Language Model (LLM) security solutions with features. Pick the best LLM security tool of your choice to fit your enterprise requirements perfectly: However, they also introduce significant risks, particularly around data security. Employees may inadvertently use levera...
Join the world’s largest applied NLP community at theNLP Summit 2022from October 4-6, 2022 to learn more about the top large language models and how they are used to solve business problems. The virtual event features three days of immersive, industry-focused content in over 50 technical se...
Taught by Prof. Chris Manning at Stanford,CS224n: Deep learning for NLPis a must-take course for anyone interested in natural language processing. From traditional NLP and linguistics concepts all the way up to large language models and ethical challenges, this course provides a comprehensive and...
多模态大语言模型(Multimodal Large Language Model,MLLM)依赖于LLM丰富的知识储备以及强大的推理和泛化能力来解决多模态问题,目前已经涌现出一些令人惊叹的能力,比如看图写作和看图写代码。但仅根据这些样例很难充分反映MLLM的性能,目前仍然缺乏对MLLM的全面评测。 因此,腾讯优图分别联合中国科学技术大学以及厦门大学,发...
As part of the OWASP AI Project, a community of experts published a list of the top 10 vulnerabilities seen in Large Language Model (LLM) applications.
7、Are Emergent Abilities of Large Language Models a Mirage?大型语言模型的涌现能力是海市蜃楼吗？涌现能力之所以吸引人，有两个方面：它们的敏锐性，似乎是瞬间从不存在到现在的转变，以及它们的不可预测性，以看似不可预见的模型规模出现。在这里，我们对涌现能力提出了另一种解释：对于特定的任务和模型族，当...
Large Language Models Encode Clinical Knowledge标题: 大型语言模型编码临床知识标签: Deepmind; Google作者: Karan Singhal,Shekoofeh Azizi,Tao Tu,S. Sara Mahdavi,Jason Wei,Hyung Won Chung,Nathan Scales,Ajay Tanwani,Heather Cole-Lewis,Stephen Pfohl,Perry Payne,Martin Seneviratne,Paul Gamble,Chris Kelly,...
更多综述细节和榜单详情,可以戳论文查看~ 多模态大模型榜单: https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models/tree/Evaluation 论文地址: [1]综述:https://arxiv.org/abs/2306.13549 [2]评测:https://arxiv.org/abs/2306.13394
首先来介绍一下什么是Large Language Model,我们应该如何去设计实验来运用这些model。 使用LLM来做推荐,大致有以下两个思路: 第一个思路是,将LLM当作backbone,利用训练时的strategy,让它去适应某一个推荐任务。例如早期的BERT4Rec,在训练的时候让模型猜测,如果少了一个item,这个item应该是什么,由模型补上这个item。
多模态大模型榜单: https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models/tree/Evaluation 论文地址: [1]综述:https://arxiv.org/abs/2306.13549 [2]评测:https://arxiv.org/abs/2306.13394 本文来源量子位,如有侵权请联系删除 END