In experiments across open-ended generation, factual QA, and mathematical reasoning, it is shown that VCM consistently mitigates the likelihood trap, and integrates with existing decoding strategies, improving diversity and coherence and, particularly at higher decoding temperatures, reasoning accuracy.
Yuanhao Ding, Meimingwei Li, E. Arias et al.· arXiv.org· 2 citations
A Concept Factorization-based Multi-View Clustering framework (CFMvC) that unifies diversity preservation, orthogonality enforcement, and manifold learning for multi-view clustering.
Qiyan Li, G. Khan, Salvador García et al.· International Journal of Dat...· 0 citations
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