3 accepted papers
Financial sentiment analysis (FSA) has attracted significant attention, and recent studies increasingly explore large language models (LLMs) for this field. Yet most work evaluates only classification metrics, leaving unclear whether sentiment signals align with market behavior. We propose FinSentLL…
Semi-supervised learning (SSL) is often hindered by learning biases when imbalanced datasets are used for training, which limits its effectiveness in real-world applications. In this paper, we propose Semi-ViM, a novel SSL framework based on Vision Mamba, a bidirectional state space model (SSM) that…
We introduce TRiCo, a novel triadic game-theoretic co-training framework that rethinks the structure of semi-supervised learning by incorporating a teacher, two students, and an adversarial generator into a unified training paradigm. Unlike existing co-training or teacher-student approaches, TRiCo f…