Author

Hao-Lun Wu

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#artificial intelligence Conference Feb 2025

Logits are All We Need to Adapt Closed Models

A token-level probability reweighting framework that, given access to logits and a small amount of task-specific data, can effectively steer black-box LLMs toward application-specific content generation and advocates for broader access to token logits in closed-source models.

G. Hiranandani, Hao-Lun Wu, Subhojyoti Mukherjee et al. · International Conference on... · 7 citations · ⚡1

Jul 2026

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation

This work introduces a unified conceptual framework that views discrete diffusion models through the construction of the underlying discrete state space, and exposes common design trade-offs across training objectives, inference algorithms, scaling behavior, systems optimization, and evaluation protocols.

Ye Yuan, Wei-En Li, Rui Song et al. · arXiv.org · 0 citations