409 citations · 483 across the 10 of their papers we have counts for
14 papers
Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation
Xu Guo, Boyang Li, Han Yu
Prompt tuning, or the conditioning of a frozen pretrained language model (PLM) with soft prompts learned from data, has demonstrated impressive performance on a wide range of NLP t…
Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
Yinan Zhang, Boyang Li, Yong Liu +2
Proper initialization is crucial to the optimization and the generalization of neural networks. However, most existing neural recommendation systems initialize the user and item em…
Noise-resistant Deep Metric Learning with Ranking-based Instance Selection
Chang Liu, Han Yu, Boyang Li +6
The existence of noisy labels in real-world data negatively impacts the performance of deep learning models. Although much research effort has been devoted to improving robustness…
Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection
Xu Guo, Boyang Li, Han Yu +1
The existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality. The adversarial neural transfer (ANT) framework utilize…
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains
Yixiao Lan, Yuan Liu, Boyang Li
The progress of deep learning (DL), especially the recent development of automatic design of networks, has brought unprecedented performance gains at heavy computational cost. On t…
Searching for Stage-wise Neural Graphs In the Limit
Xin Zhou, Dejing Dou, Boyang Li
Search space is a key consideration for neural architecture search. Recently, Xie et al. (2019) found that randomly generated networks from the same distribution perform similarly,…