An initial example in this area applied to improving ZSG is PLR (Jiang et al., 2021b),in which the sampling distribution over levels is changed to increase the learning efficiency and zero-shot generalisation of the trained policy. 可以复现一下这篇文章。 The related works of Robust RL: Chen...
we propose a new way of thinking about causality - we call this causal deep learning. The frame...
在做mask的时候,如果采用 attn_weights = where(causal_mask, attn_weights, mask_value) 这样的select操作,在昇腾硬件上是没有用加法快的,所以可以直接给要mask的位置加上一个极小值,对训练时候的值域不会产生影响 attn_weights = attn_weights + adder。 如果直接用pretrained GPT2来fine tune效果可能会很差,...
Now, any causal language model on the Hub can be evaluated in a zero-shot fashion. Zero-shot evaluation measures the likelihood of a trained model producing a given set of tokens and does not require any labelled training data, which allows researchers to skip expensive labe...
First, we describe compositional zero-shot learning from a causal perspective, and propose to view zero-shot inference as finding "which intervention caused the image?". Second, we present a causal-inspired embedding model that learns disentangled representations of elementary components of visual ...
Now, any causal language model on the Hub can be evaluated in a zero-shot fashion. Zero-shot evaluation measures the likelihood of a trained model producing a given set of tokens and does not require any labelled training data, which allows researchers to skip expensive labelling effor...
Zero-Shot Learning (ZSL) is an effective paradigm to solve label prediction when some classes have no training samples. In recent years, many ZSL algorithms have been proposed. Among them, semantic autoencoder (SAE) is widely used because of its simplicity and good generalization ability. However...
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:作者对三种主流 LLM 模型架构(Causal Decoder, CD/Non-Causal Decoder, ND/Encoder-Decoder, ED)、两种主流...
论文名称:A Causal View of Compositional Zero-Shot Recognition 来自NVIDIA的作品,今年NIPS的spotlight,再一次让人看到了Causality,特别是intervention在传统CV领域带来的新路子。 首先我们先来分析一下标题, A causal view代表了他与传统工作不同的地方,以因果为工具,我们可以避免NN带来严重的spurious correlation和泛化...
Evaluation on the Hubhelps you evaluate any model on the Hub without writing code, and is powered byAutoTrain. Now, any causal language model on the Hub can be evaluated in a zero-shot fashion. Zero-shot evaluation measures the likelihood of a trained model producing a given ...