9 papers
Towards Semantic Equivalence of Tokenization in Multimodal LLM
Shengqiong Wu, Hao Fei, Xiangtai Li +4
Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in processing vision-language tasks. One of the crux of MLLMs lies in vision tokenization, which…
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Kangkang Lu, Yanhua Yu, Hao Fei +6
In recent years, spectral graph neural networks, characterized by polynomial filters, have garnered increasing attention and have achieved remarkable performance in tasks such as n…
Conversation Disentanglement with Bi-Level Contrastive Learning
Chengyu Huang, Zheng Zhang, Hao Fei +1
Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main dr…
Enhancing Video-Language Representations with Structural Spatio-Temporal Alignment
Hao Fei, Shengqiong Wu, Meishan Zhang +3
While pre-training large-scale video-language models (VLMs) has shown remarkable potential for various downstream video-language tasks, existing VLMs can still suffer from certain…
NExT-GPT: Any-to-Any Multimodal LLM
Shengqiong Wu, Hao Fei, Leigang Qu +2
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without t…
XNLP: An Interactive Demonstration System for Universal Structured NLP
Hao Fei, Meishan Zhang, Min Zhang +1
Structured Natural Language Processing (XNLP) is an important subset of NLP that entails understanding the underlying semantic or syntactic structure of texts, which serves as a fo…