3 accepted papers
Effective multimodal learning in real-world scenarios depends on a nuanced treatment of uncertainty, which arises at three levels: (1) Intrinsic Uncertainty from modality-specific noise or ambiguity; (2) Relational Uncertainty due to cross-modal conflicts or redundancy; and (3) Aggregated Uncertaint
Mathematical reasoning poses significant challenges for Large Language Models (LLMs) due to its demand for multi-step reasoning and abstract conceptual integration. While recent test-time scaling techniques rely heavily on high-quality, challenging problems, the scarcity of Olympiad-level math probl
Understanding the relationships between items can improve the accuracy and interpretability of recommender systems. Among these relationships, the substitute and complement relationships attract the most attention in e-commerce platforms. The substitutable items are interchangeable and might be comp…