12 citations · 28 across the 7 of their papers we have counts for
7 papers
Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities
Xu Yan, Haiming Zhang, Yingjie Cai +13
The rise of large foundation models, trained on extensive datasets, is revolutionizing the field of AI. Models such as SAM, DALL-E2, and GPT-4 showcase their adaptability by extrac…
Co-training and Co-distillation for Quality Improvement and Compression of Language Models
Hayeon Lee, Rui Hou, Jongpil Kim +4
Knowledge Distillation (KD) compresses computationally expensive pre-trained language models (PLMs) by transferring their knowledge to smaller models, allowing their use in resourc…
An Early Evaluation of GPT-4V(ision)
Yang Wu, Shilong Wang, Hao Yang +4
In this paper, we evaluate different abilities of GPT-4V including visual understanding, language understanding, visual puzzle solving, and understanding of other modalities such a…
Multi-step prediction of chlorophyll concentration based on Adaptive Graph-Temporal Convolutional Network with Series Decomposition
Ying Chen, Xiao Li, Hongbo Zhang +2
Chlorophyll concentration can well reflect the nutritional status and algal blooms of water bodies, and is an important indicator for evaluating water quality. The prediction of ch…
Injecting Knowledge into Biomedical Pre-trained Models via Polymorphism and Synonymous Substitution
Hongbo Zhang, Xiang Wan, Benyou Wang
Pre-trained language models (PLMs) were considered to be able to store relational knowledge present in the training data. However, some relational knowledge seems to be discarded u…
Natural Language Reasoning, A Survey
Fei Yu, Hongbo Zhang, Prayag Tiwari +1
This survey paper proposes a clearer view of natural language reasoning in the field of Natural Language Processing (NLP), both conceptually and practically. Conceptually, we provi…