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Nicholas M. Boffi

2 papers indexed

arxivcs.CLcs.AI2026-07-01

Self-conditioned Flow Map Language Models via Fixed-point Flows

Jaehoon Yoo, Wonjung Kim, Floor Eijkelboom, Chanhyuk Lee, Nicholas M. Boffi, Seunghoon Hong, et al.

Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditioning on its own denoising estimate. While empirically successful, its performance improvements are poorly understood. Moreover, t…

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arxivcs.LGstat.ML2026-06-27

Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps

RuiKang OuYang, Hanlin Yu, Xinyue Ai, Yutong He, Nicholas M. Boffi, Pradeep Ravikumar, et al.

Recent progress in flow-based generative modeling has led to models that output high-quality samples while using only a small number of function evaluations. However, at present, there is a lack of similar advances in estimating the model likelihood. In particular, most existing…

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