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Concatenated Masked Autoencoders as Spatial-Temporal Learner
Zhouqiang Jiang, Bowen Wang, Tong Xiang +4
Learning representations from videos requires understanding continuous motion and visual correspondences between frames. In this paper, we introduce the Concatenated Masked Autoenc…
Towards Robust and Accurate Visual Prompting
Qi Li, Liangzhi Li, Zhouqiang Jiang +1
Visual prompting, an efficient method for transfer learning, has shown its potential in vision tasks. However, previous works focus exclusively on VP from standard source models, i…
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading Comprehension
Guoxin Chen, Yiming Qian, Bowen Wang +1
The large language models have achieved superior performance on various natural language tasks. One major drawback of such approaches is they are resource-intensive in fine-tuning…
TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction
Junyi Liu, Liangzhi Li, Tong Xiang +2
Since ChatGPT released its API for public use, the number of applications built on top of commercial large language models (LLMs) increase exponentially. One popular usage of such…