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Found 6 papers, 3 papers with code
Multimodal Fusion on Low-quality Data: A Comprehensive Survey
Multimodal fusion focuses on integrating information from multiple modalities with the goal of more accurate prediction, which has achieved remarkable progress in a wide range of scenarios, including autonomous driving and medical diagnosis.
TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal Content
In addition, we design a trustworthy decision mechanism that integrates subjective user perspective and objective item perspective to dynamically evaluate the uncertainty of prediction results.
Trusted Multi-view Learning with Label Noise
This motivates us to delve into a new generalized trusted multi-view learning problem: how to develop a reliable multi-view learning model under the guidance of noisy labels?
Reliable Conflictive Multi-View Learning
To solve this, we point out a new Reliable Conflictive Multi-view Learning (RCML) problem, which requires the model to provide decision results and attached reliabilities for conflictive multi-view data.
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering
The two modules can effectively utilize and enhance each other, promoting the model to learn discriminative embeddings.
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Although a few studies use multi-agent reinforcement learning to set up a cooperative game, they still suffer the following drawbacks: (1) They fail to avoid collusion solutions where all the advertisers involved in an auction collude to bid an extremely low price on purpose.
