下图是 in-context learning (左边一列)和一般 fine-tuning (右边一列)的区别,in-context learning 不产生梯度、不会更新模型参数,而 fine-tuning 会产生梯度、更新模型参数。 需要注意区分 in-context learning 中可以有 Zero-Shot、One-Shot 和 Few-Shot 的 Setting,但和 Zero-Shot learning、One-Shot learnin...
Context Aware Joint Modeling of Domain Classification, Intent Detection and Slot Filling with Zero-Shot Intent Detection ApproachNatural language understanding (NLU) aims to extract schematic information contained in user utterances, which allows down streaming module of dialogue system, i.e., Dialogue ...
We aim for zero-shot localization and classification of human actions in video. Where traditional approaches rely on global attribute or object classificat... P Mettes,CGM Snoek - IEEE 被引量: 15发表: 2017年 Jointly learning invocations and descriptions for context-aware mashup tagging with graph...
we propose a novel context-aware feature generation method for zero-shot segmentation named asCaGNet. In particular, with the observation that a pixel-wise feature highly depends on its contextual information, we insert a contextual module in a segmentation network to capture the pixel-wise contextua...
Tell me what you see: A zero-shot action recognition method based on natural language descriptions Using these representations, we build a shared semantic space employing BERT-based embedders pre-trained in the paraphrasing task on multiple text datasets... Estevam, Valter,Laroca, Rayson,Pedrini...
Iv-A1 Zero-shot Evaluation 作者需要为表1中的每个上下文类别进行二分类,并使用一种生成型的VLM方法来实现这个目标。文本提示的格式如3图所示。首先,作者在较小的_DrivingContexts(HA)_数据集上评估_ContextVLM_的性能及其适当的子集。表2中报告了每个子类别的准确率、精确率、召回率和F1分数。从表中可以看出,在...
(XMC) whose goal is to predict multiple labels for each instance from an extremely large label space. While existing research has primarily focused on fully supervised XMC, real-world scenarios often lack complete supervision signals, highlighting the importance of zero-shot settings. Given the ...
《InRanker: Distilled Rankers for Zero-shot Information Retrieval》(2024) GitHub: github.com/unicamp-dl/InRanker《War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars》(2023) GitHub: github.com/agiresearch/WarAgent [fig1]...
对于每个测试子集,我们控制了口令(passkey)的位置,使其位于输入序列的开始、中间或结尾附近。我们报告了 zero-shot 准确率(accuracy)和 fine-tuning 准确率(accuracy)。Infini-Transformers 在使用长度为 5K 的输入进行 400 步 fine-tune 后,可以解决长达 1M 的任务。
zero-shot不给任何labled数据样例，直接使用模型预测，使用的模型参数是W，few-shot给出labled数据样例，...