标题:What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? 文章链接:What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? 代码:bigscience-workshop/architecture-objective 发表:2022 领域:LLM 最优架构探索 一句话总结:作...
二,TPT+CoCoOp中,作者“可能”(咱不确定)在TPT tune the prompt的时候,没有用上CoCoOp(如下图 )的Meta-Net。 Cross-Datasets Generalization Context-dependent Visual Reasoning on Bongard-HOI Ablation Study 上面最后这张关于data augmentation的消融实验感觉不是很完整,没做CoOp和CoCoOp的。 附录中的这个定性实...
最近的研究表明,大型语言模型可以在不同的任务集上实现合理的zero-shot generalization(Brown等人,2020年)。有人假设,这是隐式多任务学习在语言模型预训练的结果(Radford等人,2019)。zero-shot能否由显式多任务学习直接实现? 为了大规模测试这个问题,我们开发了一个系统,可以轻松地将任何自然语言任务映射到人类可读的提...
InstructDoc: A Dataset for Zero-Shot Generalization of Visual Document Understanding with Instructions InstructDoc数据集:收集了30个公开的VDU数据集,涵盖了12个不同的任务,每个数据集都有专家注释的多样化指令,遵循统一的指令模式,包括用户意图和答案风格。 InstructDr模型:一个新的基于指令的文档阅读和理解模型,通...
Generalizing vision-based reinforcement learning (RL) agents to novel environments remains a difficult and open challenge. Current trends are to collect large-scale datasets or use data augmentation techniques to prevent overfitting and improve downstream generalization. However, the computational and data ...
As a step towards developing zero-shot task generalization capabilities in reinforcement learning (RL), we introduce a new RL problem where the agent should learn to execute sequences of instructions after learning useful skills that solve subtasks. In this problem, we consider two types of ...
We find that zero-shot generalization occurs during the very early stage of instruction tuning, despite the metrics chosen for measurement, while loss serves as a reasonable and suitable metric to measure zero-shot generalization due to its stability and fairness across datasets. We identify two ent...
GET-Zero- Graph Embodiment Transformer for Zero-shot Embodiment Generalization(Stanford 2024) 科技 计算机技术 人工智能 具身智能 机器学习 深度学习 mardinff 发消息 接下来播放 自动连播 Transformer本质在解决一件什么事?迪哥精讲Swin、BERT、VIT、DETR四大Transformer核心模型,究极通俗易懂! 唐宇迪深度学习 1027 ...
As a step towards developing zero-shot task generalization capabilities in reinforcement learning (RL), we introduce a new RL problem where the agent should learn to execute sequences of instructions after learning useful skills that solve subtasks. In this problem, we consider two types of gener...
The excellent generalization capability of pre-trained Vision-Language Models (VLMs) makes fine-tuning VLMs for downstream zero-shot tasks a popular choice. Despite achieving promising performance in the professionality of base classes, most existing fine-tuned methods suffer from feature confusion of ...