Papers by Yadao Wang

2 papers
Leveraging Only the Category Name for Aspect Detection through Prompt-based Constrained Clustering (2022.findings-emnlp)

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Challenge: Aspect category detection (ACD) aims to automatically identify user-concerned aspects from online reviews.
Approach: They propose a method that relies on the category name of each aspect and a pretrained language model to generate constraints for clustering.
Outcome: The proposed framework performs better than existing weakly supervised methods on nine benchmark datasets.
HyperPELT: Unified Parameter-Efficient Language Model Tuning for Both Language and Vision-and-Language Tasks (2023.findings-acl)

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Challenge: Pretraining and fine-tuning are the dominant paradigms in natural language processing.
Approach: They propose a parameter-efficient multitask learning framework that takes trainable hyper-embeddings and visual modality as input and outputs weights for different modules in a pretrained language model.
Outcome: The proposed framework adds fewer trainable parameters in multi-task learning while achieving superior performances and transfer ability compared to state-of-the-art methods.

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