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cs.CV2026
TPD: Temporal Prior Decoupling for Text-to-Video Diffusion Models
Taewon Kang, Matthias Zwicker
Text-to-video diffusion models generate temporally coherent content from natural language, yet when a prompt describes an early scene that persists while a new event emerges on top…
cs.CV2026
DCR: Counterfactual Attractor Guidance for Rare Compositional Generation
Taewon Kang, Matthias Zwicker
Diffusion models generate realistic visual content, yet often fail to produce rare but plausible compositions. When prompted with combinations that are valid but underrepresented i…
cs.CV2026
NEGATE: Constrained Semantic Guidance for Linguistic Negation in Text-to-Video Diffusion
Taewon Kang, Ming C. Lin
Negation is a fundamental linguistic operator, yet it remains inadequately modeled in diffusion-based generative systems. In this work, we present a formal treatment of linguistic…