Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot
Classification

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Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification

13 April 2022

Han Wang

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Papers citing "Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification"

7 / 7 papers shown

Title
A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics Kai He Rui Mao Qika Lin Yucheng Ruan Xiang Lan Mengling Feng Min Zhang LM&MA AILaw 230 177 0 28 Jan 2025
Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models Dohwan Ko Ji Soo Lee M. Choi Jaewon Chu Jihwan Park Hyunwoo J. Kim 55 6 0 18 Aug 2023
Language models are weak learners Hariharan Manikandan Yiding Jiang J Zico Kolter 87 19 0 25 Jun 2023
Automated Few-shot Classification with Instruction-Finetuned Language Models Rami Aly Xingjian Shi Kaixiang Lin Aston Zhang A. Wilson 75 11 0 21 May 2023
DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition Chunkit Chan Xin Liu Cheng Jiayang Zihan Li Yangqiu Song Ginny Wong Simon See 82 31 0 06 May 2023
Pre-trained Language Models Can be Fully Zero-Shot Learners Xuandong Zhao Siqi Ouyang Zhiguo Yu Ming-li Wu Lei Li VLM LRM 103 34 0 14 Dec 2022
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding Zhichao Yang Shufan Wang Bhanu Pratap Singh Rawat Avijit Mitra Hong-ye Yu 174 55 0 07 Oct 2022

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