17 citations · 73 across the 29 of their papers we have counts for
4 papers · 1 filter
Sequential Diffusion Language Models
Yangzhou Liu, Yue Cao, Hao Li +13
Diffusion language models (DLMs) have strong theoretical efficiency but are limited by fixed-length decoding and incompatibility with key-value (KV) caches. Block diffusion mitigat…
EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models
Linglin Jing, Yuting Gao, Zhigang Wang +5
Recent advancements have shown that the Mixture of Experts (MoE) approach significantly enhances the capacity of large language models (LLMs) and improves performance on downstream…
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost
Sen Xing, Muyan Zhong, Zeqiang Lai +5
In this work, we explore a cost-effective framework for multilingual image generation. We find that, unlike models tuned on high-quality images with multilingual annotations, lever…
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Weiyun Wang, Zhe Chen, Wenhai Wang +8
Existing open-source multimodal large language models (MLLMs) generally follow a training process involving pre-training and supervised fine-tuning. However, these models suffer fr…