185 citations · 1.5k across the 88 of their papers we have counts for
88 papers
Learning Unnormalized Statistical Models via Compositional Optimization
Wei Jiang, Jiayu Qin, Lingyu Wu +3
Learning unnormalized statistical models (e.g., energy-based models) is computationally challenging due to the complexity of handling the partition function. To eschew this complex…
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels
Jian Chen, Ruiyi Zhang, Tong Yu +4
Learning from noisy labels is an important and long-standing problem in machine learning for real applications. One of the main research lines focuses on learning a label corrector…
Prompt Tuning based Adapter for Vision-Language Model Adaption
Jingchen Sun, Jiayu Qin, Zihao Lin +1
Large pre-trained vision-language (VL) models have shown significant promise in adapting to various downstream tasks. However, fine-tuning the entire network is challenging due to…
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning
Qian Jiang, Changyou Chen, Han Zhao +6
Contrastive loss has been increasingly used in learning representations from multiple modalities. In the limit, the nature of the contrastive loss encourages modalities to exactly…
ALCAP: Alignment-Augmented Music Captioner
Zihao He, Weituo Hao, Wei-Tsung Lu +3
Music captioning has gained significant attention in the wake of the rising prominence of streaming media platforms. Traditional approaches often prioritize either the audio or lyr…
AUC Maximization for Low-Resource Named Entity Recognition
Ngoc Dang Nguyen, Wei Tan, Wray Buntine +3
Current work in named entity recognition (NER) uses either cross entropy (CE) or conditional random fields (CRF) as the objective/loss functions to optimize the underlying NER mode…