作者首先对完成这些任务所需要的视觉组件进行了研究,并且从(1)通用性、(2)参数效率和(3)快速适应三个方面对这些组件进行设计。为了实现与自然语言领域类似的In-Context Learning效果,作者团队首先将传统的非参数最近邻(NN)检索方法[1]拓展到密集场景预测任务中,这种基于检索的解码机制的优点就是不需要针对特定任务进行...
近来,随着ChatGPT和GPT-4等大模型的火热,使得学术界开始更多的关注于大模型背后的一些关键新技术,例如与ChatGPT高度相关的In-Context Learning(情景学习,也可以称为上下文学习)、Chain-of-thoughts(思维链推理)以及Reinforcement Learning from Human Feedback(人类反馈强化学习)等全新学习范式。在自然语言理解和生成领域,...
本文从多个角度探究了演示是如何让 In-context learning 在不同的任务中产生性能增益的,而且随着 fine-tune 阶段的黑盒化,很多文章也提出 fine-tune 阶段可能让模型丧失了泛化性,那么 ICL 这种不 fine tune 的方法既节省时间与资源开销,且能提升效果,应该会在大模型林立的时代被人关注,并迅速火起来。 往期回顾 ...
作者首先对完成这些任务所需要的视觉组件进行了研究,并且从(1)通用性、(2)参数效率和(3)快速适应三个方面对这些组件进行设计。为了实现与自然语言领域类似的In-Context Learning效果,作者团队首先将传统的非参数最近邻(NN)检索方法[1]拓展到密集场景预测任务中,这种基于检索的解码机制的优点就是不需要针对特定任务进行...
In-context learning for vision data has been underexplored compared with that in natural language. Previous works studied image in-context learning, urging models to generate a single image guided by demonstrations. In this project, we propose and study video in-context learning, where the model ...
In-context learning for vision data has been underexplored compared with that in natural language. Previous works studied image in-context learning, urging models to generate a single image guided by demonstrations. In this paper, we propose and study video in-context learning, where the model ...
Large Pre-trained Transformers exhibit an intriguing capacity for in-context learning. Without gradient updates, these models can rapidly construct new predictors from demonstrations presented in the inputs. Recent works promote this ability in the vision-language domain by incorporating visual information...
本周重要论文包括当预训练不需要注意力时,扩展到 4096 个 token 也不成问题;被 GPT 带飞的 In-Context Learning 背后是模型在秘密执行梯度下降。 目录: ClimateNeRF: Physically-based Neural Rendering for Extreme Climate Synthesis Pretraining Without Attention ...
In Large Visual Language Models (LVLMs), the efficacy of In-Context Learning (ICL) remains limited by challenges in cross-modal interactions and representation disparities. To overcome these challenges, we introduce a novel Visual In-Context Learning (VICL) method comprising Visual Demonstration Retrie...
本周重要论文包括当预训练不需要注意力时,扩展到 4096 个 token 也不成问题;被 GPT 带飞的 In-Context Learning 背后是模型在秘密执行梯度下降。 论文1:ClimateNeRF: Physically-based Neural Rendering for Extreme Climate Synthesis 作者:Yuan Li等