5 papers
Unlocking the Potentials of Retrieval-Augmented Generation for Diffusion Language Models
Chuanyue Yu, Jiahui Wang, Yuhan Li +6
Diffusion Language Models (DLMs) have recently demonstrated remarkable capabilities in natural language processing tasks. However, the potential of Retrieval-Augmented Generation (…
SparseMM: Head Sparsity Emerges from Visual Concept Responses in MLLMs
Jiahui Wang, Zuyan Liu, Yongming Rao +1
Multimodal Large Language Models (MLLMs) are commonly derived by extending pre-trained Large Language Models (LLMs) with visual capabilities. In this work, we investigate how MLLMs…
Ola: Pushing the Frontiers of Omni-Modal Language Model
Zuyan Liu, Yuhao Dong, Jiahui Wang +4
Recent advances in large language models, particularly following GPT-4o, have sparked increasing interest in developing omni-modal models capable of understanding more modalities.…
MPPO: Multi Pair-wise Preference Optimization for LLMs with Arbitrary Negative Samples
Shuo Xie, Fangzhi Zhu, Jiahui Wang +6
Aligning Large Language Models (LLMs) with human feedback is crucial for their development. Existing preference optimization methods such as DPO and KTO, while improved based on Re…
Density Distribution-based Learning Framework for Addressing Online Continual Learning Challenges
Shilin Zhang, Jiahui Wang
In this paper, we address the challenges of online Continual Learning (CL) by introducing a density distribution-based learning framework. CL, especially the Class Incremental Lear…