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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
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相关实验视频

Updated: May 15, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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Published on: December 6, 2024

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双模式 个人意识 视觉语言模型的快速调整.

Hantao Yao, Rui Zhang, Huaihai Lyu

    IEEE transactions on pattern analysis and machine intelligence
    |April 8, 2025
    PubMed
    概括

    双模式个人意识的提示调整 (BIP) 通过将先前的知识纳入提示来增强视觉语言模型. 这种新的方法提高了对各种下游任务的概括性和区分能力.

    科学领域:

    • 计算机视觉 计算机视觉
    • 自然语言处理自然语言处理.
    • 机器学习 机器学习

    背景情况:

    • 快速调整适应视觉语言模型 (VLMs) 用于诸如域泛化等任务.
    • 现有的方法从训练数据中推断提示令牌,限制适应测试数据分布.
    • 语境优化方法提高了概括性,但与测试集特定分布作斗争.

    研究的目的:

    • 引入双模式个人意识的快速调整 (BIP) 以提高VLM的适应性.
    • 将个人先前的知识纳入可学习提示中,以提高可区分性和概括性.
    • 开发一种新的方法,使VLM能够更有效地适应各种下游任务.

    主要方法:

    • BIP使用文本知识嵌入 (TKE) 和视觉知识嵌入 (VKE) 模型.
    • 将类意识的文本知识项目转化为类意识提示 (TCP) 和实例意识的知识转化为实例意识提示 (VIP).
    • TCP 动态调整未见域的分类器; VIP 增强视觉嵌入的可辨性.

    主要成果:

    • 在四个不同的任务中,BIP在15个基准指标中表现优异.
    • 该方法在概括和区分能力方面取得了显著的改进.
    • 评估证实了BIP作为一个plug-and-play模块的有效性.

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    结论:

    • BIP提供了一种新且有效的方法,用于对VLMs进行快速调整.
    • 整合个人先前知识显著提高模型性能.
    • BIP 作为一个多功能且易于集成的模块,用于现有的 VLM 框架.