no code implementations • Findings (EMNLP) 2021 • Jia Chen, Yike Wu, Shiwan Zhao, Qin Jin
Our analysis of caption models with SC loss shows that the performance degradation is caused by the increasingly noisy estimation of reward and baseline with fewer language resources.
no code implementations • 8 Apr 2024 • Jichang Yang, Hegan Chen, Jia Chen, Songqi Wang, Shaocong Wang, Yifei Yu, Xi Chen, Bo wang, Xinyuan Zhang, Binbin Cui, Ning Lin, Meng Xu, Yi Li, Xiaoxin Xu, Xiaojuan Qi, Zhongrui Wang, Xumeng Zhang, Dashan Shang, Han Wang, Qi Liu, Kwang-Ting Cheng, Ming Liu
Demonstrating equivalent generative quality to the software baseline, our system achieved remarkable enhancements in generative speed for both unconditional and conditional generation tasks, by factors of 64. 8 and 156. 5, respectively.
no code implementations • 27 Mar 2024 • Yan Fang, Jingtao Zhan, Qingyao Ai, Jiaxin Mao, Weihang Su, Jia Chen, Yiqun Liu
In this study, we investigate whether the performance of dense retrieval models follows the scaling law as other neural models.
1 code implementation • 27 Mar 2024 • Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jia Chen, Shaoping Ma
Our in-depth analysis of these logs reveals that user prompt reformulation is heavily dependent on the individual user's capability, resulting in significant variance in the quality of reformulation pairs.
no code implementations • 27 Mar 2024 • Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Zhijing Wu, Yiqun Liu, Chong Chen, Qi Tian
However, general LLMs, which are developed on open-domain data, may lack the domain-specific knowledge essential for tasks in vertical domains, such as legal, medical, etc.
no code implementations • 27 Mar 2024 • Haitao Li, Qingyao Ai, Xinyan Han, Jia Chen, Qian Dong, Yiqun Liu, Chong Chen, Qi Tian
Most of the existing works focus on improving the representation ability for the contextualized embedding of the [CLS] token and calculate relevance using textual semantic similarity.
1 code implementation • 17 Dec 2023 • Weihang Su, Qingyao Ai, Xiangsheng Li, Jia Chen, Yiqun Liu, Xiaolong Wu, Shengluan Hou
With the development of deep learning and natural language processing techniques, pre-trained language models have been widely used to solve information retrieval (IR) problems.
no code implementations • 14 Dec 2023 • Shaocong Wang, Yizhao Gao, Yi Li, Woyu Zhang, Yifei Yu, Bo wang, Ning Lin, Hegan Chen, Yue Zhang, Yang Jiang, Dingchen Wang, Jia Chen, Peng Dai, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Xiaoxin Xu, Hayden So, Zhongrui Wang, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu
Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks.
no code implementations • 1 Dec 2023 • Biqian Cheng, Evangelos E. Papalexakis, Jia Chen
Canonical Correlation Analysis (CCA) has been widely applied to jointly embed multiple views of data in a maximally correlated latent space.
no code implementations • 25 Nov 2023 • Rutuja Gurav, Het Patel, Zhuocheng Shang, Ahmed Eldawy, Jia Chen, Elia Scudiero, Evangelos Papalexakis
This paper attempts to highlight a use-case of state-of-the-art image segmentation models like SAM for crop-type mapping and related specific needs of the agriculture industry, offering a potential avenue for automatic, efficient, and cost-effective data products for precision agriculture practices.
1 code implementation • 25 Apr 2023 • Jia Chen, Haitao Li, Weihang Su, Qingyao Ai, Yiqun Liu
This paper introduces the approaches we have used to participate in the WSDM Cup 2023 Task 1: Unbiased Learning to Rank.
1 code implementation • 22 Apr 2023 • Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Yueyue Wu, Yiqun Liu, Chong Chen, Qi Tian
Moreover, in contrast to the general retrieval, the relevance in the legal domain is sensitive to key legal elements.
no code implementations • 23 Mar 2023 • Xiaorong Yang, Jia Chen, Degui Li, Runze Li
A latent group structure is imposed on the heterogenous quantile regression models so that the number of nonparametric functional coefficients to be estimated can be reduced considerably.
no code implementations • 10 Mar 2023 • Xinyi Zhang, Zhuo Chang, Hong Wu, Yang Li, Jia Chen, Jian Tan, Feifei Li, Bin Cui
To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents cognizant of each other.
no code implementations • 28 Feb 2023 • Haitao Li, Jia Chen, Weihang Su, Qingyao Ai, Yiqun Liu
This paper describes the approach of the THUIR team at the WSDM Cup 2023 Pre-training for Web Search task.
no code implementations • 23 Feb 2023 • Jia Chen, Yixian Chun, Yuanyi Liu, Renyu Zhang, Yang Hu
High-Dimensional and Incomplete matrices, which usually contain a large amount of valuable latent information, can be well represented by a Latent Factor Analysis model.
no code implementations • 23 Feb 2023 • Jia Chen, Renyu Zhang, Yuanyi Liu
Recently, Swarm Intelligence-related LFA models have been proposed and adopted widely to improve the optimization process of LFA with high efficiency, i. e., the Particle Swarm Optimization (PSO)-LFA model.
no code implementations • 13 Aug 2022 • Yuanyi Liu, Jia Chen, Di wu
The A2BAS algorithm consists of two sub-algorithms.
no code implementations • 2 Apr 2022 • Jia Chen, Di wu, Xin Luo
High-dimensional and sparse (HiDS) matrices are frequently adopted to describe the complex relationships in various big data-related systems and applications.
no code implementations • 27 Nov 2021 • Yixing Fan, Xiaohui Xie, Yinqiong Cai, Jia Chen, Xinyu Ma, Xiangsheng Li, Ruqing Zhang, Jiafeng Guo
The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to the user's information need.
no code implementations • 4 Oct 2021 • Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu
The successes of most previous methods heavily rely on rich node features and high-fidelity labels.
no code implementations • 27 Apr 2021 • Xian-Feng Han, Zhang-Yue He, Jia Chen, Guo-Qiang Xiao
First, a point-wise feature pyramid module is introduced to hierarchically extract features from different scales or resolutions.
no code implementations • 29 Mar 2021 • Guotong Xue, Ming Zhong, JianXin Li, Jia Chen, Chengshuai Zhai, Ruochen Kong
Due to the lack of comprehensive investigation of them, we give a survey of dynamic network embedding in this paper.
no code implementations • NeurIPS 2020 • Deheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, Yinyuting Yin, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu
However, existing work falls short in handling the raw game complexity caused by the explosion of agent combinations, i. e., lineups, when expanding the hero pool in case that OpenAI's Dota AI limits the play to a pool of only 17 heroes.
no code implementations • 17 Aug 2020 • Jia Chen, Evangelos E. Papalexakis
Node embeddings have been attracting increasing attention during the past years.
no code implementations • 14 Mar 2020 • Xinyi Zeng, Qian Zhang, Jia Chen, Guixu Zhang, Aimin Zhou, Yiqin Wang
Finally, the proposed hybrid loss in a four hierarchy-pixel, patch, map and boundary guides the network to effectively segment the tongue regions and accurate tongue boundaries.
no code implementations • CVPR 2020 • Jia Chen, Qin Jin
In this work, we show the limitation of the current sequence-level learning objective for captioning tasks from both theory and empirical result.
no code implementations • 21 Aug 2019 • Yike Wu, Shiwan Zhao, Jia Chen, Ying Zhang, Xiaojie Yuan, Zhong Su
Improving the captioning performance on low-resource languages by leveraging English caption datasets has received increasing research interest in recent years.
no code implementations • 29 Nov 2018 • Jia Chen, Gang Wang, Georgios B. Giannakis
common sources).
no code implementations • 15 May 2018 • Jia Chen, Gang Wang, Georgios B. Giannakis
Under certain conditions, dPCA is proved to be least-squares optimal in recovering the component vector unique to the target data relative to background data.
no code implementations • 27 Mar 2018 • Jia Chen, Gang Wang, Yanning Shen, Georgios B. Giannakis
Canonical correlation analysis (CCA) is a powerful technique for discovering whether or not hidden sources are commonly present in two (or more) datasets.
no code implementations • 25 Oct 2017 • Gang Wang, Jia Chen, Georgios B. Giannakis
Principal component analysis (PCA) has well-documented merits for data extraction and dimensionality reduction.
no code implementations • 31 Aug 2017 • Shizhe Chen, Jia Chen, Qin Jin
In addition to predefined topics, i. e., category tags crawled from the web, we also mine topics in a data-driven way based on training captions by an unsupervised topic mining model.
no code implementations • 31 Aug 2017 • Shizhe Chen, Jia Chen, Qin Jin, Alexander Hauptmann
For the topic prediction task, we use the mined topics as the teacher to train a student topic prediction model, which learns to predict the latent topics from multimodal contents of videos.
no code implementations • 19 Apr 2014 • Jie Shen, Guangcan Liu, Jia Chen, Yuqiang Fang, Jianbin Xie, Yong Yu, Shuicheng Yan
In this paper, we utilize structured learning to simultaneously address two intertwined problems: human pose estimation (HPE) and garment attribute classification (GAC), which are valuable for a variety of computer vision and multimedia applications.