Learning to Classify Intents and Slot Labels Given a Handful of Examples

Learning to Classify Intents and Slot Labels Given a Handful of Examples

22 April 2020

Papers citing "Learning to Classify Intents and Slot Labels Given a Handful of Examples"

10 / 10 papers shown

Title
Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent Classification Mujeen Sung James Gung Elman Mansimov Nikolaos Pappas Raphael Shu Salvatore Romeo Yi Zhang Vittorio Castelli 31 7 0 24 May 2023
TOKEN is a MASK: Few-shot Named Entity Recognition with Pre-trained Language Models A. Davody David Ifeoluwa Adelani Thomas Kleinbauer Dietrich Klakow 22 4 0 15 Jun 2022
NLU++: A Multi-Label, Slot-Rich, Generalisable Dataset for Natural Language Understanding in Task-Oriented Dialogue I. Casanueva Ivan Vulić Georgios P. Spithourakis Paweł Budzianowski 27 10 0 27 Apr 2022
MGIMN: Multi-Grained Interactive Matching Network for Few-shot Text Classification Jianhai Zhang M. Maimaiti Xing Gao Yuanhang Zheng Ji Zhang 16 9 0 11 Apr 2022
Few-shot Named Entity Recognition with Cloze Questions V. Gatta V. Moscato Marco Postiglione Giancarlo Sperlí 19 4 0 24 Nov 2021
Controllable Semantic Parsing via Retrieval Augmentation Panupong Pasupat Yuan Zhang Kelvin Guu 132 47 0 16 Oct 2021
MCML: A Novel Memory-based Contrastive Meta-Learning Method for Few Shot Slot Tagging Hongru Wang Zezhong Wang Gabriel Pui Cheong Fung Kam-Fai Wong OffRL CLL 27 10 0 26 Aug 2021
Language Model is All You Need: Natural Language Understanding as Question Answering Mahdi Namazifar Alexandros Papangelis Gokhan Tur Dilek Z. Hakkani-Tür 21 47 0 05 Nov 2020
Few-shot Learning for Multi-label Intent Detection Yutai Hou Y. Lai Yushan Wu Wanxiang Che Ting Liu VLM 21 48 0 11 Oct 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017