1 code implementation • 5 Mar 2024 • Xiangyu Li, Xinjie Shen, Yawen Zeng, Xiaofen Xing, Jin Xu
However, compared with financial institutions, it is not easy for ordinary investors to mine factors and analyze news.
Ranked #1 on Stock Market Prediction on Astock
1 code implementation • 23 Jan 2024 • Ru Peng, Heming Zou, Haobo Wang, Yawen Zeng, Zenan Huang, Junbo Zhao
The core of the MDE is to establish a meta-distribution statistic, on the information (energy) associated with individual samples, then offer a smoother representation enabled by energy-based learning.
no code implementations • 28 Dec 2023 • Yajing Zhai, Yawen Zeng, Zhiyong Huang, Zheng Qin, Xin Jin, Da Cao
Thereby, this paper explores the potential of using the generated multiple person attributes as prompts in ReID tasks with off-the-shelf (large) models for more accurate retrieval results.
1 code implementation • 30 Jul 2023 • Keyu Pan, Yawen Zeng
The field of large language models (LLMs) has made significant progress, and their knowledge storage capacity is approaching that of human beings.
1 code implementation • 21 Apr 2023 • Ru Peng, Yawen Zeng, Junbo Zhao
Sign language translation (SLT) systems, which are often decomposed into video-to-gloss (V2G) recognition and gloss-to-text (G2T) translation through the pivot gloss, heavily relies on the availability of large-scale parallel G2T pairs.
1 code implementation • 10 Oct 2022 • Ru Peng, Yawen Zeng, Junbo Zhao
Thus, in this work, we introduce IKD-MMT, a novel MMT framework to support the image-free inference phase via an inversion knowledge distillation scheme.
Ranked #2 on Multimodal Machine Translation on Multi30K
2 code implementations • 29 Oct 2021 • Ning Han, Jingjing Chen, Chuhao Shi, Yawen Zeng, Guangyi Xiao, Hao Chen
The task of text-video retrieval aims to understand the correspondence between language and vision, has gained increasing attention in recent years.
no code implementations • CVPR 2021 • Yawen Zeng, Da Cao, Xiaochi Wei, Meng Liu, Zhou Zhao, Zheng Qin
Toward this end, we contribute a multi-modal relational graph to capture the interactions among objects from the visual and textual content to identify the differences among similar video moment candidates.