We propose a new zero-shot CNN evaluation index based on this robustness index.Chisato TakahashiKenya Jin'noJournal of Signal Processing (1342-6230)
2021. Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models. arXiv preprint arXiv:2104.08663. [3] Ma et al. 2021. Zero-shot neural passage retrieval via domain-targeted synthetic question generation. In Proceedings of the 16th Conference of the European Chapter ...
Zero- and Few-shot Named Entity Recognition and Text Expansion in Medication Prescriptions using ChatGPT Introduction: Medication prescriptions are often in free text and include a mix of two languages, local brand names, and a wide range of idiosyncratic form... N Isaradech,A Riedel,W Siri...
原文如下: Creating a perfectly unbiased evaluationdatasetfor retrieval is inherently complex and is subject to multiple biases induced by the: (i) annotation guidelines, (ii) annotation setup, and by the (iii) human annotators. Further, it is impossible to manually annotate the relevance for all...
首先在包括commonsense reasoning、machine translation、sentiment analysis等NLP task上进行微调,然后在从未见过的natural language inference任务上进行zero-shot evaluation Instruction-tuning与Fine-tuning和Prompt-Tuning的对比: Pretrain-Finetune:现在大规模语料上根据某一个(几个)训练目标进行预训练,然后主...
- 另一个新的零样本学习的基准是**Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly**,它是一个对现有零样本学习方法进行了全面评估和分析的工作,提出了一个统一的评估协议和数据划分,涵盖了13个不同领域和任务的数据集。它的基准是根据模型在未见类别上的分类准确率和泛化能...
EvaluationoftheGood,theBadandtheUgly YongqinXian,StudentMember,IEEE,ChristophH.Lampert, BerntSchiele,Fellow,IEEE,andZeynepAkata,Member,IEEE Abstract—Duetotheimportanceofzero-shotlearning,i.e.classifyingimageswherethereisalackoflabeledtrainingdata,the ...
马普所在论文Evaluation of output embeddings for fine-grained image classification中衡量了多种不同Semantic embedding对ZSL的效果。然而该论文对各种Semantic Embedding的来龙去脉甚为含糊,后续的研究中也鲜有提及。为了搞清楚各种不同的知识来源的来龙去脉,我们回顾马普所的系列研究中的经典论文之二:Evaluating Knowledg...
In this work, we propose an evaluation procedure that enables fair use of external data for zero-shot action recognition. We empirically show that external sources tend to have actions excessively similar to the target classes, strongly influencing the performance and violating the zero-shot premise...
First, given the fact that there is no agreed upon zero-shot learning benchmark, we first define a new benchmark by unifying both the evaluation protocols and data splits. This is an important contribution as published results are often not comparable and sometimes even flawed due to, e.g....