5 papers · 1 filter
dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
Zhiyuan Liu, Yicun Yang, Yaojie Zhang +6
Autoregressive Models (ARMs) have long dominated the landscape of Large Language Models. Recently, a new paradigm has emerged in the form of diffusion-based Large Language Models (…
DISA: Offline Importance Sampling for Distribution-Matching LLM-RL
Shaobo Wang, Yujie Chen, Yafeng Sun +9
Modern reasoning agents are increasingly evaluated on their ability to generate multiple valid solution paths, plans, or tool-use traces for a given input. Standard reward-maximizi…
Grounding and Enhancing Informativeness and Utility in Dataset Distillation
Shaobo Wang, Yantai Yang, Guo Chen +5
Dataset Distillation (DD) seeks to create a compact dataset from a large, real-world dataset. While recent methods often rely on heuristic approaches to balance efficiency and qual…
SpeCa: Accelerating Diffusion Transformers with Speculative Feature Caching
Jiacheng Liu, Chang Zou, Yuanhuiyi Lyu +4
Diffusion models have revolutionized high-fidelity image and video synthesis, yet their computational demands remain prohibitive for real-time applications. These models face two f…
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers
Shaobo Wang, Hongxuan Tang, Mingyang Wang +5
The debate between self-interpretable models and post-hoc explanations for black-box models is central to Explainable AI (XAI). Self-interpretable models, such as concept-based net…