9 papers
Cluster-Based Generalized Additive Models Informed by Random Fourier Features
Xin Huang, Jia Li, Jun Yu
In developing data-driven modeling methodologies, there is an ongoing need to reconcile the strong predictive performance of opaque black-box models with the transparency required…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
BayesRAG: Probabilistic Mutual Evidence Corroboration for Multimodal Retrieval-Augmented Generation
Xuan Li, Yining Wang, Haocai Luo +6
Retrieval-Augmented Generation (RAG) has become a pivotal paradigm for Large Language Models (LLMs), yet current approaches struggle with visually rich documents by treating text a…
Semi-Supervised Facial Expression Recognition based on Dynamic Threshold and Negative Learning
Zhongpeng Cai, Jun Yu, Wei Xu +3
Facial expression recognition is a key task in human-computer interaction and affective computing. However, acquiring a large amount of labeled facial expression data is often cost…
Multimodal Sentiment Analysis based on Multi-channel and Symmetric Mutual Promotion Feature Fusion
Wangyuan Zhu, Jun Yu
Multimodal sentiment analysis is a key technology in the fields of human-computer interaction and affective computing. Accurately recognizing human emotional states is crucial for…
MIAR: Modality Interaction and Alignment Representation Fuison for Multimodal Emotion
Jichao Zhu, Jun Yu
Multimodal Emotion Recognition (MER) aims to perceive human emotions through three modes: language, vision, and audio. Previous methods primarily focused on modal fusion without ad…