Timely Survey
Timely surveys in various scientific fields analyze the current state-of-the-art in specific areas, aiming to synthesize existing research and identify key trends. Current research focuses on efficient model variants for tasks like image segmentation and 3D vision, leveraging architectures such as diffusion models and large language models (LLMs) to improve performance and address challenges in resource-constrained environments or low-resource languages. These surveys are crucial for guiding future research directions, facilitating the development of more efficient and robust algorithms, and ultimately impacting the practical application of these technologies across diverse domains.
Papers
RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methods
Xin Qiao, Matteo Poggi, Pengchao Deng, Hao Wei, Chenyang Ge, Stefano Mattoccia
Networking Systems for Video Anomaly Detection: A Tutorial and Survey
Jing Liu, Yang Liu, Jieyu Lin, Jielin Li, Peng Sun, Bo Hu, Liang Song, Azzedine Boukerche, Victor C. M. Leung
A survey on fairness of large language models in e-commerce: progress, application, and challenge
Qingyang Ren, Zilin Jiang, Jinghan Cao, Sijia Li, Chiqu Li, Yiyang Liu, Shuning Huo, Tiange He, Yuan Chen
A Survey On Text-to-3D Contents Generation In The Wild
Chenhan Jiang
A Survey of Generative Techniques for Spatial-Temporal Data Mining
Qianru Zhang, Haixin Wang, Cheng Long, Liangcai Su, Xingwei He, Jianlong Chang, Tailin Wu, Hongzhi Yin, Siu-Ming Yiu, Qi Tian, Christian S. Jensen
A Survey on Transformers in NLP with Focus on Efficiency
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
A Survey of Large Language Models for Graphs
Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh Chawla, Chao Huang
Deep video representation learning: a survey
Elham Ravanbakhsh, Yongqing Liang, J. Ramanujam, Xin Li
A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, Qing Li
Anomaly Detection in Graph Structured Data: A Survey
Prabin B Lamichhane, William Eberle