6.1. Generalization to Held-Out Tasks 我们想搞清楚的第一个问题是,multitask prompted training能否提升held-out任务上的泛化性。结果如下:对比T0和T5+LM,由于二者的区别仅在于,是否采用了multitask prompted training,因此,multi-task训练对效果的提升是显而易见的。
总结 本文的结果表现了当前对于prompt的使用在multi-task训练中仍存在很大的空间,同时prompt为multi-view learning、ensemble等提供了很好的切入点。将这样的约束进一步放到上游训练中而不仅是在下游测试,也许能带来进一步的增强。 论文地址:https://openreview.net/pdf/2a8357b141dcf79c07623f4e329c953901e06c69.pdf...
今天给大家介绍一篇由42位作者共同参与的论文《Multitask Prompted Training Enables Zero-Shot Task Generalization》这篇论文由Hugging Face牵头，如果用一连串数字来概括这篇论文，我们就会发现“大力真的可以创造奇迹”：· 一共收集了171个多任务数据集，总共创建了1939个prompt，平均每个数据集有11.3个prompt；· 共...
文| JayJay 前几天,JayJay刷到一篇NB的paper《Multitask Prompted Training Enables Zero-Shot Task Generalization》,共有42位作者参与,实属巨制: 这篇论文由Hugging Face牵头,如果用一连串数字来概括这篇论文,我们就会发现“大力真的可以创造奇迹”: 一共收集了171个多任务数据集,总共创建了1939个prompt,平均每个...
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 ...
然而，这种设定要求模型参数量庞大，并且对提示敏感。本文旨在通过显式的多任务监督学习，探索是否能促进小规模参数模型在未见过任务上的泛化能力，同时降低模型对提示的敏感度。实验通过混合多种自然语言处理任务进行训练，目标是使模型在特定任务上表现更佳，同时确保模型对提示的适应性。为了将各种NLP任务...
前几天,JayJay刷到一篇NB的paper《Multitask Prompted Training Enables Zero-Shot Task Generalization》,共有42位作者参与,实属巨制: 这篇论文由Hugging Face牵头,如果用一连串数字来概括这篇论文,我们就会发现“大力真的可以创造奇迹”: 一共收集了171个多任务数据集,总共创建了1939个prompt,平均每个数据集有11.3个...
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...
Multitask Prompted Training Enables Zero-Shot Task Generalization 论文链接: https://arxiv.org/abs/2110.08207 2.1 Motivation T0 和 FLAN 工作整体相似,区别是增加了任务和 prompt 数量,FLAN 使用了 decoder-only,T0 使用了 encoder+decoder,FLAN 每次针对测试一个任务训练一个模型,其他任务作为训练集,T0 为了测...
Large language models have recently been shown to attain reasonable zero-shotgeneralization on a diverse set of tasks. It has been hypothesized that this isa consequence of implicit multitask learning in language model training. Canzero-shot generalization instead be directly induced by explicit multi...