6 papers
Mixture of States: Routing Token-Level Dynamics for Multimodal Generation
Haozhe Liu, Ding Liu, Mingchen Zhuge +16
We introduce MoS (Mixture of States), a novel fusion paradigm for multimodal diffusion models that merges modalities using flexible, state-based interactions. The core of MoS is a…
Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers
Andrew Nam, Henry Conklin, Yukang Yang +3
We present causal head gating (CHG), a scalable method for interpreting the functional roles of attention heads in transformer models. CHG learns soft gates over heads and assigns…
Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models
Yingqing Guo, Yukang Yang, Hui Yuan +1
Training-free guidance enables controlled generation in diffusion and flow models, but most methods rely on gradients and assume differentiable objectives. This work focuses on tra…
Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models
Yukang Yang, Declan Campbell, Kaixuan Huang +3
Many recent studies have found evidence for emergent reasoning capabilities in large language models (LLMs), but debate persists concerning the robustness of these capabilities, an…
Gradient Guidance for Diffusion Models: An Optimization Perspective
Yingqing Guo, Hui Yuan, Yukang Yang +2
Diffusion models have demonstrated empirical successes in various applications and can be adapted to task-specific needs via guidance. This paper studies a form of gradient guidanc…
Latent Diffusion Models for Controllable RNA Sequence Generation
Kaixuan Huang, Yukang Yang, Kaidi Fu +3
This work presents RNAdiffusion, a latent diffusion model for generating and optimizing discrete RNA sequences of variable lengths. RNA is a key intermediary between DNA and protei…