Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Haode, Liang, Haowen, Zhan, Liming, Lam, Albert Y. S., Wu, Xiao-Ming |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization
by: Zhang, Haode, et al.
Published: (2022)
by: Zhang, Haode, et al.
Published: (2022)
Effectiveness of Pre-training for Few-shot Intent Classification
by: Zhang, Haode, et al.
Published: (2021)
by: Zhang, Haode, et al.
Published: (2021)
New Intent Discovery with Pre-training and Contrastive Learning
by: Zhang, Yuwei, et al.
Published: (2022)
by: Zhang, Yuwei, et al.
Published: (2022)
Minimizing PLM-Based Few-Shot Intent Detectors
by: Zhang, Haode, et al.
Published: (2024)
by: Zhang, Haode, et al.
Published: (2024)
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection
by: Liu, Bo, et al.
Published: (2024)
by: Liu, Bo, et al.
Published: (2024)
Structure-aware Fine-tuning for Code Pre-trained Models
by: Wu, Jiayi, et al.
Published: (2024)
by: Wu, Jiayi, et al.
Published: (2024)
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler
by: Mirza, Paramita, et al.
Published: (2024)
by: Mirza, Paramita, et al.
Published: (2024)
IntentGPT: Few-shot Intent Discovery with Large Language Models
by: Rodriguez, Juan A., et al.
Published: (2024)
by: Rodriguez, Juan A., et al.
Published: (2024)
Dental Severity Assessment through Few-shot Learning and SBERT Fine-tuning
by: Dehghani, Mohammad
Published: (2024)
by: Dehghani, Mohammad
Published: (2024)
Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition
by: Yao, Zheng, et al.
Published: (2025)
by: Yao, Zheng, et al.
Published: (2025)
RIFF: Learning to Rephrase Inputs for Few-shot Fine-tuning of Language Models
by: Najafi, Saeed, et al.
Published: (2024)
by: Najafi, Saeed, et al.
Published: (2024)
Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction
by: Wang, Xiaokai, et al.
Published: (2025)
by: Wang, Xiaokai, et al.
Published: (2025)
Continual Dialogue State Tracking via Reason-of-Select Distillation
by: Feng, Yujie, et al.
Published: (2024)
by: Feng, Yujie, et al.
Published: (2024)
Adaptive Few-shot Prompting for Machine Translation with Pre-trained Language Models
by: Tang, Lei, et al.
Published: (2025)
by: Tang, Lei, et al.
Published: (2025)
Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?
by: Zeng, Hansi, et al.
Published: (2025)
by: Zeng, Hansi, et al.
Published: (2025)
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages
by: Bahad, Sankalp, et al.
Published: (2024)
by: Bahad, Sankalp, et al.
Published: (2024)
Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors
by: Ma, Shengkun, et al.
Published: (2024)
by: Ma, Shengkun, et al.
Published: (2024)
Learning to Learn for Few-shot Continual Active Learning
by: Ho, Stella, et al.
Published: (2023)
by: Ho, Stella, et al.
Published: (2023)
Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuning
by: Zhang, Hengyuan, et al.
Published: (2024)
by: Zhang, Hengyuan, et al.
Published: (2024)
Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features
by: Fan, Miao, et al.
Published: (2024)
by: Fan, Miao, et al.
Published: (2024)
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
by: Song, Weixi, et al.
Published: (2023)
by: Song, Weixi, et al.
Published: (2023)
SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations
by: Solano, Jesus, et al.
Published: (2023)
by: Solano, Jesus, et al.
Published: (2023)
Intent-driven In-context Learning for Few-shot Dialogue State Tracking
by: Yi, Zihao, et al.
Published: (2024)
by: Yi, Zihao, et al.
Published: (2024)
Neural-Bayesian Program Learning for Few-shot Dialogue Intent Parsing
by: Hong, Mengze, et al.
Published: (2024)
by: Hong, Mengze, et al.
Published: (2024)
Pre-trained Language Models Improve the Few-shot Prompt Ability of Decision Transformer
by: Yang, Yu, et al.
Published: (2024)
by: Yang, Yu, et al.
Published: (2024)
Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot
by: Cheng, Xiang, et al.
Published: (2025)
by: Cheng, Xiang, et al.
Published: (2025)
Enhancing Fact Retrieval in PLMs through Truthfulness
by: Youssef, Paul, et al.
Published: (2024)
by: Youssef, Paul, et al.
Published: (2024)
MEDVOC: Vocabulary Adaptation for Fine-tuning Pre-trained Language Models on Medical Text Summarization
by: Balde, Gunjan, et al.
Published: (2024)
by: Balde, Gunjan, et al.
Published: (2024)
RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules
by: Li, Miaomiao, et al.
Published: (2024)
by: Li, Miaomiao, et al.
Published: (2024)
SPAFIT: Stratified Progressive Adaptation Fine-tuning for Pre-trained Large Language Models
by: Arora, Samir, et al.
Published: (2024)
by: Arora, Samir, et al.
Published: (2024)
Pre-training, Fine-tuning and Re-ranking: A Three-Stage Framework for Legal Question Answering
by: Ni, Shiwen, et al.
Published: (2024)
by: Ni, Shiwen, et al.
Published: (2024)
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification
by: Park, Gyutae, et al.
Published: (2024)
by: Park, Gyutae, et al.
Published: (2024)
The Queen of England is not England's Queen: On the Lack of Factual Coherency in PLMs
by: Youssef, Paul, et al.
Published: (2024)
by: Youssef, Paul, et al.
Published: (2024)
MLPs Compass: What is learned when MLPs are combined with PLMs?
by: Zhou, Li, et al.
Published: (2024)
by: Zhou, Li, et al.
Published: (2024)
QASE Enhanced PLMs: Improved Control in Text Generation for MRC
by: Ai, Lin, et al.
Published: (2024)
by: Ai, Lin, et al.
Published: (2024)
Probing Critical Learning Dynamics of PLMs for Hate Speech Detection
by: Masud, Sarah, et al.
Published: (2024)
by: Masud, Sarah, et al.
Published: (2024)
Audio Contrastive-based Fine-tuning: Decoupling Representation Learning and Classification
by: Wang, Yang, et al.
Published: (2023)
by: Wang, Yang, et al.
Published: (2023)
Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers
by: Nguyen, Tuc, et al.
Published: (2024)
by: Nguyen, Tuc, et al.
Published: (2024)
Semi-supervised Fine-tuning for Large Language Models
by: Luo, Junyu, et al.
Published: (2024)
by: Luo, Junyu, et al.
Published: (2024)
Bridging the Gap: Transfer Learning from English PLMs to Malaysian English
by: Chanthran, Mohan Raj, et al.
Published: (2024)
by: Chanthran, Mohan Raj, et al.
Published: (2024)
Similar Items
-
Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization
by: Zhang, Haode, et al.
Published: (2022) -
Effectiveness of Pre-training for Few-shot Intent Classification
by: Zhang, Haode, et al.
Published: (2021) -
New Intent Discovery with Pre-training and Contrastive Learning
by: Zhang, Yuwei, et al.
Published: (2022) -
Minimizing PLM-Based Few-Shot Intent Detectors
by: Zhang, Haode, et al.
Published: (2024) -
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection
by: Liu, Bo, et al.
Published: (2024)