TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification

17 October 2023

Papers citing "TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification"

6 / 6 papers shown

Title
ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification J. Chen Richong Zhang Yongyi Mao Jie Xue 27 78 0 16 May 2023
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 221 862 0 15 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 141 62 0 12 Oct 2021
Semi-Supervised Few-Shot Intent Classification and Slot Filling S. Basu Karine lp Kiun Chong Amr Sharaf Alex Fischer Vishal Rohra Michael Amoake Hazem El-Hammamy Ehimwenma Nosakhare Vijay Ramani Benjamin Han VLM 16 6 0 17 Sep 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 212 508 0 15 Jan 2021
Efficient Intent Detection with Dual Sentence Encoders I. Casanueva Tadas Temvcinas D. Gerz Matthew Henderson Ivan Vulić VLM 178 451 0 10 Mar 2020