MCLR: improving conditional modeling in visual generative models via inter-class likelihood-ratio maximization and establishing the equivalence between classifier-free guidance and alignment objectives. Li, X., Jia, Y., Li, X., Fessler, J. A., Wang, R., & Qu, Q. 2026.
MCLR: improving conditional modeling in visual generative models via inter-class likelihood-ratio maximization and establishing the equivalence between classifier-free guidance and alignment objectives [link]Paper  bibtex   
@MISC{li:26:mic-arxiv,
 author = {X. Li and Y. Jia and X. Li and J. A. Fessler and R. Wang and Q. Qu},
 title = {{MCLR:} improving conditional modeling in visual generative models via inter-class likelihood-ratio maximization and establishing the equivalence between classifier-free guidance and alignment objectives},
 url = {http://arxiv.org/abs/2603.22364},
 year = 2026
}

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