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Inducer-tuning: Connecting Prefix-tuning and Adapter-tuning
Yifan Chen, Devamanyu Hazarika, Mahdi Namazifar +3
Prefix-tuning, or more generally continuous prompt tuning, has become an essential paradigm of parameter-efficient transfer learning. Using a large pre-trained language model (PLM)…
Analyzing Modality Robustness in Multimodal Sentiment Analysis
Devamanyu Hazarika, Yingting Li, Bo Cheng +3
Building robust multimodal models are crucial for achieving reliable deployment in the wild. Despite its importance, less attention has been paid to identifying and improving the r…
So Different Yet So Alike! Constrained Unsupervised Text Style Transfer
Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan +2
Automatic transfer of text between domains has become popular in recent times. One of its aims is to preserve the semantic content of text being translated from source to target do…
Empowering parameter-efficient transfer learning by recognizing the kernel structure in self-attention
Yifan Chen, Devamanyu Hazarika, Mahdi Namazifar +3
The massive amount of trainable parameters in the pre-trained language models (PLMs) makes them hard to be deployed to multiple downstream tasks. To address this issue, parameter-e…