A comprehensive evaluation of ChatGPT’s zero-shot Text-to-SQL capability论文笔记 Peking2025 2 人赞同了该文章 论文地址:github.com/THU-BPM/chat. Spider 数据集(Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task) Spider-SYN(Gan et al...
语言模型做规划——Language Models as Zero-Shot Planners论文速读 tanh 清华计算机系本+博士生 AI OIer 古典音乐、历史爱好者 4 人赞同了该文章 Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentswenlong.page/language-pby...
2. Related work Our work relates to diverse themes in the litera- ture including zero-shot semantic/instance segmentation, unsupervised semantic segmentation (with and without language-image pretraining), unsupervised object segmen- tation, class-agnostic unsupervised instance segmentation...
Zero-shot Cross-lingual EAE has garnered significant interests from the community because it could minimize the need for extensive data annotation to identify the roles of the arguments within a specific event. Some prior works point out that syntactic structures could be regarded as the language-...
Zero-Shot Learning (ZSL) for visual recognition is typically achieved by exploiting a semantic embedding space. In such a space, both seen and unseen class labels as well as image features can be embedded so that the similarity among them can be measured directly. In this work, we consider ...
[CVPR 2018 论文笔记] Preserving Semantic Relations for Zero-Shot Learning,程序员大本营,技术文章内容聚合第一站。
In this paper, we propose an embarrassingly simple yet highly effective zero-shot semantic segmentation (ZS3) method, based on the pre-trained vision-language model CLIP. First, our study provides a couple of key discoveries: (i) the global tokens (a.k.a [CLS] tokens in Transformer) of ...
inference, sentiment analysis, semantic role labeling, zero-shot relation extraction, goal-oriented dialogue, semantic parsing, and commonsense pronoun resolution... B Mccann,NS Keskar,C Xiong,... 被引量: 36发表: 2018年 加载更多0关于我们 百度学术集成海量学术资源,融合人工智能、深度学习、大数据分析...
In addition, this paper provides some discussions on open challenges that few/zero-shot learning brought to visual semantic segmentation, such as cross-domain few/zero-shot segmentation and generalized few/zero-shot segmentation. In summary, the main contributions of this paper are as follows: 1)...
Akata, Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly, 2017, arXiv preprint arXiv:1707.00600. Google Scholar [37] Palatucci M., Pomerleau D., Hinton G.E., Mitchell T.M. Zero-shot learning with semantic output codes Advances in Neural Information Processing...