Papers with VPT

2 papers
Comprehensive Study of Bilingual and Multi-category Instruction Pre-training (2026.findings-eacl)

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Challenge: Instruction pre-training (IPT) has recently gained attention as an intermediate stage between pre- and post-training for large language models.
Approach: They study the optimal balance between raw and instruction-response data, languages, and task categories in an LLM instruction-respondence dataset.
Outcome: The proposed model improves on English-centric and bilingual models using bilingual instruction-response datasets.
Visual Prompt Tuning for Few-Shot Text Classification (2022.coling-1)

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Challenge: Existing work on pretraining models for text classification uses image encoders instead of visual prompts.
Approach: They propose a method to deploy large-scale pre-trained models in the prompt-tuning paradigm in few-shot learning.
Outcome: The proposed method outperforms the most recent prompt-tuning methods on five public text classification datasets.

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