no code implementations • 7 Mar 2014 • Zhiwu Lu, Zhen-Yong Fu, Tao Xiang, Li-Wei Wang, Ji-Rong Wen
By oversegmenting all the images into regions, we formulate noisily tagged image parsing as a weakly supervised sparse learning problem over all the regions, where the initial labels of each region are inferred from image-level labels.
no code implementations • 18 Jan 2015 • Zhiwu Lu, Li-Wei Wang, Ji-Rong Wen
This paper presents a new framework for visual bag-of-words (BOW) refinement and reduction to overcome the drawbacks associated with the visual BOW model which has been widely used for image classification.
1 code implementation • 6 Feb 2015 • Wayne Xin Zhao, Xu-Dong Zhang, Daniel Lemire, Dongdong Shan, Jian-Yun Nie, Hongfei Yan, Ji-Rong Wen
Compression algorithms are important for data oriented tasks, especially in the era of Big Data.
no code implementations • 18 Feb 2015 • Jiajun Liu, Kun Zhao, Brano Kusy, Ji-Rong Wen, Raja Jurdak
The prediction of periodical time-series remains challenging due to various types of data distortions and misalignments.
no code implementations • 4 Jul 2017 • Aoxue Li, Zhiwu Lu, Li-Wei Wang, Tao Xiang, Xinqi Li, Ji-Rong Wen
In this paper, to address the two issues, we propose a two-phase framework for recognizing images from unseen fine-grained classes, i. e. zero-shot fine-grained classification.
no code implementations • 5 Sep 2017 • Yulei Niu, Zhiwu Lu, Ji-Rong Wen, Tao Xiang, Shih-Fu Chang
In this paper, we address two main issues in large-scale image annotation: 1) how to learn a rich feature representation suitable for predicting a diverse set of visual concepts ranging from object, scene to abstract concept; 2) how to annotate an image with the optimal number of class labels.
no code implementations • 8 Oct 2017 • Yanlei Yu, Zhiwu Lu, Jiajun Liu, Guoping Zhao, Ji-Rong Wen, Kai Zheng
We propose a novel network representations learning model framework called RUM (network Representation learning throUgh Multi-level structural information preservation).
1 code implementation • 30 Jul 2018 • Wayne Xin Zhao, Gaole He, Hongjian Dou, Jin Huang, Siqi Ouyang, Ji-Rong Wen
Based on our linked dataset, we first preform some interesting qualitative analysis experiments, in which we discuss the effect of two important factors (i. e. popularity and recency) on whether a RS item can be linked to a KB entity.
no code implementations • NeurIPS 2018 • An Zhao, Mingyu Ding, Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen
This is made possible by learning a projection between a feature space and a semantic space (e. g. attribute space).
no code implementations • 19 Oct 2018 • Zhiwu Lu, Jiechao Guan, Aoxue Li, Tao Xiang, An Zhao, Ji-Rong Wen
Specifically, we assume that each synthesised data point can belong to any unseen class; and the most likely two class candidates are exploited to learn a robust projection function in a competitive fashion.
no code implementations • 19 Oct 2018 • Aoxue Li, Zhiwu Lu, Jiechao Guan, Tao Xiang, Li-Wei Wang, Ji-Rong Wen
Inspired by the fact that an unseen class is not exactly `unseen' if it belongs to the same superclass as a seen class, we propose a novel inductive ZSL model that leverages superclasses as the bridge between seen and unseen classes to narrow the domain gap.
1 code implementation • CVPR 2019 • Yulei Niu, Hanwang Zhang, Manli Zhang, Jianhong Zhang, Zhiwu Lu, Ji-Rong Wen
Visual dialog is a challenging vision-language task, which requires the agent to answer multi-round questions about an image.
Ranked #13 on Visual Dialog on VisDial v0.9 val
no code implementations • CVPR 2019 • Mingyu Ding, An Zhao, Zhiwu Lu, Tao Xiang, Ji-Rong Wen
To address the training data scarcity problem, our FFCSN model is trained with both meta learning and adversarial learning.
no code implementations • 11 Dec 2018 • Nanyi Fei, Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen
The standard approach to ZSL requires a set of training images annotated with seen class labels and a semantic descriptor for seen/unseen classes (attribute vector is the most widely used).
no code implementations • 12 Feb 2019 • Ting Bai, Pan Du, Wayne Xin Zhao, Ji-Rong Wen, Jian-Yun Nie
Recommending the right products is the central problem in recommender systems, but the right products should also be recommended at the right time to meet the demands of users, so as to maximize their values.
no code implementations • 14 Apr 2019 • Jingxuan Yang, Jun Xu, Jianzhuo Tong, Sheng Gao, Jun Guo, Ji-Rong Wen
In the offline phase, IERT pre-trains deep item representations conditioning on their transaction contexts.
1 code implementation • ACL 2019 • Junyi Li, Wayne Xin Zhao, Ji-Rong Wen, Yang song
In this paper, we propose a novel review generation model by characterizing an elaborately designed aspect-aware coarse-to-fine generation process.
no code implementations • 12 Jul 2019 • Guoping Zhao, Mingyu Zhang, Jiajun Liu, Ji-Rong Wen
Such tendency indicates that the model indeed learned how to toy with both image retrieval systems and human eyes.
no code implementations • 20 Aug 2019 • Songwei Ge, Zhicheng Dou, Zhengbao Jiang, Jian-Yun Nie, Ji-Rong Wen
Our analysis reveals that the attention model is able to attribute higher weights to more related past sessions after fine training.
no code implementations • 27 Aug 2019 • Yuqi Huo, Xiaoli Xu, Yao Lu, Yulei Niu, Zhiwu Lu, Ji-Rong Wen
In addition to motion vectors, we also provide a temporal fusion method to explicitly induce the temporal context.
no code implementations • IJCNLP 2019 • Shuqing Bian, Wayne Xin Zhao, Yang song, Tao Zhang, Ji-Rong Wen
Furthermore, we extend the match network and implement domain adaptation in three levels, sentence-level representation, sentence-level match, and global match.
no code implementations • IJCNLP 2019 • Siqing Li, Wayne Xin Zhao, Eddy Jing Yin, Ji-Rong Wen
An important kind of data signals, peer review text, has not been utilized for the CCP task.
2 code implementations • 12 Dec 2019 • Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xue-Qi Cheng, Ji-Rong Wen
In learning-to-rank for information retrieval, a ranking model is automatically learned from the data and then utilized to rank the sets of retrieved documents.
no code implementations • 6 Feb 2020 • Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen
Specifically, armed with a set transformer based attention module, we construct each episode with two sub-episodes without class overlap on the seen classes to simulate the domain shift between the seen and unseen classes.
no code implementations • 11 Feb 2020 • Nanyi Fei, Zhiwu Lu, Yizhao Gao, Jia Tian, Tao Xiang, Ji-Rong Wen
In this paper, we argue that the inter-meta-task relationships should be exploited and those tasks are sampled strategically to assist in meta-learning.
no code implementations • 18 Feb 2020 • Kun Zhou, Wayne Xin Zhao, Yutao Zhu, Ji-Rong Wen, Jingsong Yu
Open-domain retrieval-based dialogue systems require a considerable amount of training data to learn their parameters.
no code implementations • 28 Feb 2020 • Jianhong Zhang, Manli Zhang, Zhiwu Lu, Tao Xiang, Ji-Rong Wen
To address this problem, we propose a graph convolutional network (GCN)-based label denoising (LDN) method to remove the irrelevant images.
1 code implementation • 19 Mar 2020 • An Zhao, Mingyu Ding, Zhiwu Lu, Tao Xiang, Yulei Niu, Jiechao Guan, Ji-Rong Wen, Ping Luo
Existing few-shot learning (FSL) methods make the implicit assumption that the few target class samples are from the same domain as the source class samples.
4 code implementations • 28 Mar 2020 • Gaole He, Junyi Li, Wayne Xin Zhao, Peiju Liu, Ji-Rong Wen
Our generator is isolated from user interaction data, and serves to improve the performance of the discriminator.
2 code implementations • 21 May 2020 • Ruiyang Ren, Zhao-Yang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, Ji-Rong Wen
Recently, deep learning has made significant progress in the task of sequential recommendation.
1 code implementation • CVPR 2021 • Yulei Niu, Kaihua Tang, Hanwang Zhang, Zhiwu Lu, Xian-Sheng Hua, Ji-Rong Wen
VQA models may tend to rely on language bias as a shortcut and thus fail to sufficiently learn the multi-modal knowledge from both vision and language.
2 code implementations • 8 Jul 2020 • Kun Zhou, Wayne Xin Zhao, Shuqing Bian, Yuanhang Zhou, Ji-Rong Wen, Jingsong Yu
Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations.
Ranked #3 on Text Generation on ReDial
no code implementations • 25 Jul 2020 • Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang, Xiaohui Yan, Ji-Rong Wen
Deep Q-learning algorithms often suffer from poor gradient estimations with an excessive variance, resulting in unstable training and poor sampling efficiency.
2 code implementations • 18 Aug 2020 • Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Ji-Rong Wen
To tackle this problem, we propose the model S^3-Rec, which stands for Self-Supervised learning for Sequential Recommendation, based on the self-attentive neural architecture.
no code implementations • 19 Aug 2020 • Kun Zhou, Wayne Xin Zhao, Hui Wang, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Ji-Rong Wen
Most of the existing CRS methods focus on learning effective preference representations for users from conversation data alone.
no code implementations • 25 Sep 2020 • Shuqing Bian, Xu Chen, Wayne Xin Zhao, Kun Zhou, Yupeng Hou, Yang song, Tao Zhang, Ji-Rong Wen
Compared with pure text-based matching models, the proposed approach is able to learn better data representations from limited or even sparse interaction data, which is more resistible to noise in training data.
2 code implementations • 28 Sep 2020 • Hongjin Qian, Xiaohe Li, Hanxun Zhong, Yu Guo, Yueyuan Ma, Yutao Zhu, Zhanliang Liu, Zhicheng Dou, Ji-Rong Wen
This enables the development of personalized dialogue models that directly learn implicit user personality from the user's dialogue history.
1 code implementation • 4 Oct 2020 • Junyi Li, Siqing Li, Wayne Xin Zhao, Gaole He, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Ji-Rong Wen, Nianwen Xue
Exploratory analysis also demonstrates that the GCRF did help to capture the dependencies between pronouns in neighboring utterances, thus contributes to the performance improvements.
2 code implementations • COLING 2020 • Kun Zhou, Yuanhang Zhou, Wayne Xin Zhao, Xiaoke Wang, Ji-Rong Wen
To develop an effective CRS, the support of high-quality datasets is essential.
no code implementations • 9 Oct 2020 • Wayne Xin Zhao, Junhua Chen, Pengfei Wang, Qi Gu, Ji-Rong Wen
Top-N item recommendation has been a widely studied task from implicit feedback.
1 code implementation • EMNLP 2020 • Weijie Yu, Chen Xu, Jun Xu, Liang Pang, Xiaopeng Gao, Xiaozhao Wang, Ji-Rong Wen
Four popular text matching methods have been exploited in the paper.
1 code implementation • NeurIPS 2020 • Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen
Most notably, GBP can deliver superior performance on a graph with over 60 million nodes and 1. 8 billion edges in less than half an hour on a single machine.
1 code implementation • 3 Nov 2020 • Wayne Xin Zhao, Shanlei Mu, Yupeng Hou, Zihan Lin, Yushuo Chen, Xingyu Pan, Kaiyuan Li, Yujie Lu, Hui Wang, Changxin Tian, Yingqian Min, Zhichao Feng, Xinyan Fan, Xu Chen, Pengfei Wang, Wendi Ji, Yaliang Li, Xiaoling Wang, Ji-Rong Wen
In this library, we implement 73 recommendation models on 28 benchmark datasets, covering the categories of general recommendation, sequential recommendation, context-aware recommendation and knowledge-based recommendation.
no code implementations • 1 Jan 2021 • Yuqi Huo, Mingyu Ding, Haoyu Lu, Zhiwu Lu, Tao Xiang, Ji-Rong Wen, Ziyuan Huang, Jianwen Jiang, Shiwei Zhang, Mingqian Tang, Songfang Huang, Ping Luo
With the constrained jigsaw puzzles, instead of solving them directly, which could still be extremely hard, we carefully design four surrogate tasks that are more solvable but meanwhile still ensure that the learned representation is sensitive to spatiotemporal continuity at both the local and global levels.
1 code implementation • ACL 2021 • Kun Zhou, Xiaolei Wang, Yuanhang Zhou, Chenzhan Shang, Yuan Cheng, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen
In recent years, conversational recommender system (CRS) has received much attention in the research community.
1 code implementation • ACL 2021 • Junyi Li, Tianyi Tang, Gaole He, Jinhao Jiang, Xiaoxuan Hu, Puzhao Xie, Zhipeng Chen, Zhuohao Yu, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we release an open-source library, called TextBox, to provide a unified, modularized, and extensible text generation framework.
1 code implementation • 11 Jan 2021 • Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen
In our approach, the student network aims to find the correct answer to the query, while the teacher network tries to learn intermediate supervision signals for improving the reasoning capacity of the student network.
Ranked #2 on Semantic Parsing on WebQuestionsSP
2 code implementations • 11 Mar 2021 • Yuqi Huo, Manli Zhang, Guangzhen Liu, Haoyu Lu, Yizhao Gao, Guoxing Yang, Jingyuan Wen, Heng Zhang, Baogui Xu, Weihao Zheng, Zongzheng Xi, Yueqian Yang, Anwen Hu, Jinming Zhao, Ruichen Li, Yida Zhao, Liang Zhang, Yuqing Song, Xin Hong, Wanqing Cui, Danyang Hou, Yingyan Li, Junyi Li, Peiyu Liu, Zheng Gong, Chuhao Jin, Yuchong Sun, ShiZhe Chen, Zhiwu Lu, Zhicheng Dou, Qin Jin, Yanyan Lan, Wayne Xin Zhao, Ruihua Song, Ji-Rong Wen
We further construct a large Chinese multi-source image-text dataset called RUC-CAS-WenLan for pre-training our BriVL model.
Ranked #1 on Image Retrieval on RUC-CAS-WenLan
no code implementations • 9 May 2021 • Junyi Li, Wayne Xin Zhao, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
For global coherence, we design a hierarchical self-attentive architecture with both subgraph- and node-level attention to enhance the correlations between subgraphs.
no code implementations • 21 May 2021 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we present an overview of the major advances achieved in the topic of PLMs for text generation.
no code implementations • 25 May 2021 • Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we elaborately summarize the typical challenges and solutions for complex KBQA.
1 code implementation • Findings (ACL) 2021 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
This paper studies how to automatically generate a natural language text that describes the facts in knowledge graph (KG).
1 code implementation • ACL 2021 • Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Z. Y. Xie, Zhong-Yi Lu, Ji-Rong Wen
This paper presents a novel pre-trained language models (PLM) compression approach based on the matrix product operator (short as MPO) from quantum many-body physics.
1 code implementation • ACL 2021 • Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Nianwen Xue, Ji-Rong Wen
A second (multi-relational) GCN is then applied to the utterance states to produce a discourse relation-augmented representation for the utterances, which are then fused together with token states in each utterance as input to a dropped pronoun recovery layer.
Ranked #5 on Discourse Parsing on STAC
no code implementations • 12 Jun 2021 • Hui Wang, Kun Zhou, Wayne Xin Zhao, Jingyuan Wang, Ji-Rong Wen
Due to the flexibility in modelling data heterogeneity, heterogeneous information network (HIN) has been adopted to characterize complex and heterogeneous auxiliary data in top-$N$ recommender systems, called \emph{HIN-based recommendation}.
no code implementations • 14 Jun 2021 • Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Yuan YAO, Ao Zhang, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI).
1 code implementation • 26 Jul 2021 • Bing Su, Ji-Rong Wen
Convolutional neural networks use regular quadrilateral convolution kernels to extract features.
no code implementations • ACL 2021 • Chongyang Tao, Changyu Chen, Jiazhan Feng, Ji-Rong Wen, Rui Yan
Recently, many studies are emerging towards building a retrieval-based dialogue system that is able to effectively leverage background knowledge (e. g., documents) when conversing with humans.
1 code implementation • 2 Aug 2021 • Konrad Heidler, Lichao Mou, Di Hu, Pu Jin, Guangyao Li, Chuang Gan, Ji-Rong Wen, Xiao Xiang Zhu
By fine-tuning the models on a number of commonly used remote sensing datasets, we show that our approach outperforms existing pre-training strategies for remote sensing imagery.
Ranked #2 on Cross-Modal Retrieval on SoundingEarth
no code implementations • 12 Aug 2021 • Lin Bo, Liang Pang, Gang Wang, Jun Xu, Xiuqiang He, Ji-Rong Wen
Experimental results base on three publicly available benchmarks showed that in both of the implementations, Pre-Rank can respectively outperform the underlying ranking models and achieved state-of-the-art performances.
1 code implementation • Findings (ACL) 2021 • Ruiyang Ren, Shangwen Lv, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qiaoqiao She, Hua Wu, Haifeng Wang, Ji-Rong Wen
Recently, dense passage retrieval has become a mainstream approach to finding relevant information in various natural language processing tasks.
1 code implementation • 15 Aug 2021 • Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB).
1 code implementation • 18 Aug 2021 • Hongjin Qian, Zhicheng Dou, Yutao Zhu, Yueyuan Ma, Ji-Rong Wen
To learn a user's personalized language style, we elaborately build language models from shallow to deep using the user's historical responses; To model a user's personalized preferences, we explore the conditional relations underneath each post-response pair of the user.
1 code implementation • 20 Aug 2021 • Zhengyi Ma, Zhicheng Dou, Yutao Zhu, Hanxun Zhong, Ji-Rong Wen
Specifically, leveraging the benefits of Transformer on language understanding, we train a personalized language model to construct a general user profile from the user's historical responses.
1 code implementation • 20 Aug 2021 • Zhengyi Ma, Zhicheng Dou, Wei Xu, Xinyu Zhang, Hao Jiang, Zhao Cao, Ji-Rong Wen
In this paper, we propose to leverage the large-scale hyperlinks and anchor texts to pre-train the language model for ad-hoc retrieval.
1 code implementation • EMNLP 2021 • Kun Zhou, Wayne Xin Zhao, Sirui Wang, Fuzheng Zhang, Wei Wu, Ji-Rong Wen
To solve this issue, various data augmentation techniques are proposed to improve the robustness of PLMs.
1 code implementation • ICLR 2022 • Bing Su, Ji-Rong Wen
Explainable distances for sequence data depend on temporal alignment to tackle sequences with different lengths and local variances.
no code implementations • 29 Sep 2021 • Bing Su, Ji-Rong Wen
Convolutional neural networks use regular quadrilateral convolution kernels to extract features.
no code implementations • 29 Sep 2021 • Ze-Feng Gao, Peiyu Liu, Xiao-Hui Zhang, Xin Zhao, Z. Y. Xie, Zhong-Yi Lu, Ji-Rong Wen
Based on the MPS structure, we propose a new dataset compression method that compresses datasets by filtering long-range correlation information in task-agnostic scenarios and uses dataset distillation to supplement the information in task-specific scenarios.
no code implementations • 30 Sep 2021 • Jing Yao, Zhicheng Dou, Ruobing Xie, Yanxiong Lu, Zhiping Wang, Ji-Rong Wen
Search and recommendation are the two most common approaches used by people to obtain information.
1 code implementation • EMNLP 2021 • Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qiaoqiao She, Hua Wu, Haifeng Wang, Ji-Rong Wen
In this paper, we propose a novel joint training approach for dense passage retrieval and passage re-ranking.
1 code implementation • 27 Oct 2021 • Nanyi Fei, Zhiwu Lu, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, Hao Sun, Ji-Rong Wen
To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks.
1 code implementation • 24 Nov 2021 • Yujia Zhou, Zhicheng Dou, Yutao Zhu, Ji-Rong Wen
Personalized search plays a crucial role in improving user search experience owing to its ability to build user profiles based on historical behaviors.
no code implementations • NeurIPS 2021 • Yuqi Huo, Mingyu Ding, Haoyu Lu, Nanyi Fei, Zhiwu Lu, Ji-Rong Wen, Ping Luo
To enhance the representation ability of the motion vectors, hence the effectiveness of our method, we design a cross guidance contrastive learning algorithm based on multi-instance InfoNCE loss, where motion vectors can take supervision signals from RGB frames and vice versa.
1 code implementation • 22 Dec 2021 • Di Hu, Yake Wei, Rui Qian, Weiyao Lin, Ruihua Song, Ji-Rong Wen
To address this problem, we propose a two-stage step-by-step learning framework to localize and recognize sounding objects in complex audiovisual scenarios using only the correspondence between audio and vision.
no code implementations • 14 Jan 2022 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
We begin with introducing three key aspects of applying PLMs to text generation: 1) how to encode the input into representations preserving input semantics which can be fused into PLMs; 2) how to design an effective PLM to serve as the generation model; and 3) how to effectively optimize PLMs given the reference text and to ensure that the generated texts satisfy special text properties.
1 code implementation • COLING 2022 • Tianyi Tang, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen
Secondly, we use continuous inverse prompting to improve the process of natural language generation by modeling an inverse generation process from output to input, making the generated text more relevant to the inputs.
1 code implementation • 4 Feb 2022 • Mingguo He, Zhewei Wei, Ji-Rong Wen
GPR-GNN and BernNet demonstrate that the Monomial and Bernstein bases also outperform the Chebyshev basis in terms of learning the spectral graph convolutions.
1 code implementation • 9 Feb 2022 • Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang song, Ji-Rong Wen
In this paper, we propose a model-agnostic framework named IV4Rec that can effectively decompose the embedding vectors into these two parts, hence enhancing recommendation results.
no code implementations • 14 Feb 2022 • Xu Chen, Yongfeng Zhang, Ji-Rong Wen
Beyond summarizing the previous work, we also analyze the (dis)advantages of existing evaluation methods and provide a series of guidelines on how to select them.
2 code implementations • 28 Feb 2022 • Kun Zhou, Hui Yu, Wayne Xin Zhao, Ji-Rong Wen
Recently, deep neural networks such as RNN, CNN and Transformer have been applied in the task of sequential recommendation, which aims to capture the dynamic preference characteristics from logged user behavior data for accurate recommendation.
no code implementations • 1 Mar 2022 • Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Wu, Ji-Rong Wen
Web search provides a promising way for people to obtain information and has been extensively studied.
2 code implementations • COLING 2022 • Ze-Feng Gao, Peiyu Liu, Wayne Xin Zhao, Zhong-Yi Lu, Ji-Rong Wen
Recently, Mixture-of-Experts (short as MoE) architecture has achieved remarkable success in increasing the model capacity of large-scale language models.
1 code implementation • 3 Mar 2022 • Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen
In this way, we can learn adaptive representations for a given graph when paired with different graphs, and both node- and graph-level characteristics are naturally considered in a single pre-training task.
1 code implementation • ACL 2022 • Quan Tu, Yanran Li, Jianwei Cui, Bin Wang, Ji-Rong Wen, Rui Yan
Applying existing methods to emotional support conversation -- which provides valuable assistance to people who are in need -- has two major limitations: (a) they generally employ a conversation-level emotion label, which is too coarse-grained to capture user's instant mental state; (b) most of them focus on expressing empathy in the response(s) rather than gradually reducing user's distress.
1 code implementation • CVPR 2022 • Guangyao Li, Yake Wei, Yapeng Tian, Chenliang Xu, Ji-Rong Wen, Di Hu
In this paper, we focus on the Audio-Visual Question Answering (AVQA) task, which aims to answer questions regarding different visual objects, sounds, and their associations in videos.
Ranked #5 on Audio-visual Question Answering on MUSIC-AVQA
no code implementations • 26 Mar 2022 • Sha Yuan, Hanyu Zhao, Shuai Zhao, Jiahong Leng, Yangxiao Liang, Xiaozhi Wang, Jifan Yu, Xin Lv, Zhou Shao, Jiaao He, Yankai Lin, Xu Han, Zhenghao Liu, Ning Ding, Yongming Rao, Yizhao Gao, Liang Zhang, Ming Ding, Cong Fang, Yisen Wang, Mingsheng Long, Jing Zhang, Yinpeng Dong, Tianyu Pang, Peng Cui, Lingxiao Huang, Zheng Liang, HuaWei Shen, HUI ZHANG, Quanshi Zhang, Qingxiu Dong, Zhixing Tan, Mingxuan Wang, Shuo Wang, Long Zhou, Haoran Li, Junwei Bao, Yingwei Pan, Weinan Zhang, Zhou Yu, Rui Yan, Chence Shi, Minghao Xu, Zuobai Zhang, Guoqiang Wang, Xiang Pan, Mengjie Li, Xiaoyu Chu, Zijun Yao, Fangwei Zhu, Shulin Cao, Weicheng Xue, Zixuan Ma, Zhengyan Zhang, Shengding Hu, Yujia Qin, Chaojun Xiao, Zheni Zeng, Ganqu Cui, Weize Chen, Weilin Zhao, Yuan YAO, Peng Li, Wenzhao Zheng, Wenliang Zhao, Ziyi Wang, Borui Zhang, Nanyi Fei, Anwen Hu, Zenan Ling, Haoyang Li, Boxi Cao, Xianpei Han, Weidong Zhan, Baobao Chang, Hao Sun, Jiawen Deng, Chujie Zheng, Juanzi Li, Lei Hou, Xigang Cao, Jidong Zhai, Zhiyuan Liu, Maosong Sun, Jiwen Lu, Zhiwu Lu, Qin Jin, Ruihua Song, Ji-Rong Wen, Zhouchen Lin, LiWei Wang, Hang Su, Jun Zhu, Zhifang Sui, Jiajun Zhang, Yang Liu, Xiaodong He, Minlie Huang, Jian Tang, Jie Tang
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.
no code implementations • 27 Mar 2022 • Yupeng Hou, Xingyu Pan, Wayne Xin Zhao, Shuqing Bian, Yang song, Tao Zhang, Ji-Rong Wen
As the core technique of online recruitment platforms, person-job fit can improve hiring efficiency by accurately matching job positions with qualified candidates.
no code implementations • 1 Apr 2022 • Zhenlei Wang, Xu Chen, Rui Zhou, Quanyu Dai, Zhenhua Dong, Ji-Rong Wen
The key of sequential recommendation lies in the accurate item correlation modeling.
no code implementations • 2 Apr 2022 • Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen
An extension to the pairwise neural ranking is also developed.
1 code implementation • 6 Apr 2022 • Tingchen Fu, Xueliang Zhao, Chongyang Tao, Ji-Rong Wen, Rui Yan
In this work, we introduce personal memory into knowledge selection in KGC to address the personalization issue.
no code implementations • CVPR 2022 • Haoyu Lu, Nanyi Fei, Yuqi Huo, Yizhao Gao, Zhiwu Lu, Ji-Rong Wen
Under a fair comparison setting, our COTS achieves the highest performance among all two-stream methods and comparable performance (but with 10, 800X faster in inference) w. r. t.
Ranked #23 on Video Retrieval on MSR-VTT
no code implementations • NAACL 2022 • Hanxun Zhong, Zhicheng Dou, Yutao Zhu, Hongjin Qian, Ji-Rong Wen
Existing personalized dialogue systems have tried to extract user profiles from dialogue history to guide personalized response generation.
no code implementations • 27 Apr 2022 • Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qifei Wu, Yuchen Ding, Hua Wu, Haifeng Wang, Ji-Rong Wen
Recent years have witnessed the significant advance in dense retrieval (DR) based on powerful pre-trained language models (PLM).
1 code implementation • ACL 2022 • Kun Zhou, Beichen Zhang, Wayne Xin Zhao, Ji-Rong Wen
In DCLR, we design an instance weighting method to punish false negatives and generate noise-based negatives to guarantee the uniformity of the representation space.
1 code implementation • NAACL 2022 • Junyi Li, Tianyi Tang, Zheng Gong, Lixin Yang, Zhuohao Yu, Zhipeng Chen, Jingyuan Wang, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we present a large-scale empirical study on general language ability evaluation of PLMs (ElitePLM).
1 code implementation • NAACL 2022 • Junyi Li, Tianyi Tang, Jian-Yun Nie, Ji-Rong Wen, Wayne Xin Zhao
First, PTG learns a set of source prompts for various source generation tasks and then transfers these prompts as target prompts to perform target generation tasks.
1 code implementation • 4 May 2022 • Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
Commonsense reasoning in natural language is a desired ability of artificial intelligent systems.
no code implementations • 1 Jun 2022 • Lanling Xu, Jianxun Lian, Wayne Xin Zhao, Ming Gong, Linjun Shou, Daxin Jiang, Xing Xie, Ji-Rong Wen
The learn-to-compare paradigm of contrastive representation learning (CRL), which compares positive samples with negative ones for representation learning, has achieved great success in a wide range of domains, including natural language processing, computer vision, information retrieval and graph learning.
no code implementations • 10 Jun 2022 • Zihan Lin, Hui Wang, Jingshu Mao, Wayne Xin Zhao, Cheng Wang, Peng Jiang, Ji-Rong Wen
Relevant recommendation is a special recommendation scenario which provides relevant items when users express interests on one target item (e. g., click, like and purchase).
1 code implementation • 13 Jun 2022 • Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen
In order to develop effective sequential recommenders, a series of sequence representation learning (SRL) methods are proposed to model historical user behaviors.
1 code implementation • 13 Jun 2022 • Wayne Xin Zhao, Kun Zhou, Zheng Gong, Beichen Zhang, Yuanhang Zhou, Jing Sha, Zhigang Chen, Shijin Wang, Cong Liu, Ji-Rong Wen
Considering the complex nature of mathematical texts, we design a novel curriculum pre-training approach for improving the learning of mathematical PLMs, consisting of both basic and advanced courses.
2 code implementations • 15 Jun 2022 • Wayne Xin Zhao, Yupeng Hou, Xingyu Pan, Chen Yang, Zeyu Zhang, Zihan Lin, Jingsen Zhang, Shuqing Bian, Jiakai Tang, Wenqi Sun, Yushuo Chen, Lanling Xu, Gaowei Zhang, Zhen Tian, Changxin Tian, Shanlei Mu, Xinyan Fan, Xu Chen, Ji-Rong Wen
In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures.
1 code implementation • 19 Jun 2022 • Xiaolei Wang, Kun Zhou, Ji-Rong Wen, Wayne Xin Zhao
Our approach unifies the recommendation and conversation subtasks into the prompt learning paradigm, and utilizes knowledge-enhanced prompts based on a fixed pre-trained language model (PLM) to fulfill both subtasks in a unified approach.
Ranked #1 on Text Generation on ReDial
2 code implementations • 24 Jun 2022 • Tianyi Tang, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen
Motivated by the success of supervised pre-training, we propose Multi-task superVised Pre-training (MVP) for natural language generation.
1 code implementation • 9 Jul 2022 • Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, Ji-Rong Wen
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems.
no code implementations • 15 Aug 2022 • Guoping Zhao, Bingqing Zhang, Mingyu Zhang, Yaxian Li, Jiajun Liu, Ji-Rong Wen
It models a video with a lattice feature graph in which the nodes represent regions of different granularity, with weighted edges that represent the spatial and temporal links.
1 code implementation • 17 Aug 2022 • Haoyu Lu, Qiongyi Zhou, Nanyi Fei, Zhiwu Lu, Mingyu Ding, Jingyuan Wen, Changde Du, Xin Zhao, Hao Sun, Huiguang He, Ji-Rong Wen
Further, from the perspective of neural encoding (based on our foundation model), we find that both visual and lingual encoders trained multimodally are more brain-like compared with unimodal ones.
1 code implementation • 18 Aug 2022 • Chen Yang, Yupeng Hou, Yang song, Tao Zhang, Ji-Rong Wen, Wayne Xin Zhao
To model the two-way selection preference from the dual-perspective of job seekers and employers, we incorporate two different nodes for each candidate (or job) and characterize both successful matching and failed matching via a unified dual-perspective interaction graph.
no code implementations • 19 Aug 2022 • Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Wu, Peitian Zhang, Ji-Rong Wen
In order to unify these two stages, we explore a model-based indexer for document retrieval.
1 code implementation • 23 Aug 2022 • Haonan Chen, Zhicheng Dou, Yutao Zhu, Zhao Cao, Xiaohua Cheng, Ji-Rong Wen
To help the encoding of the current user behavior sequence, we propose to use a decoder and the information of future sequences and a supplemental query.
4 code implementations • 12 Sep 2022 • Bing Su, Dazhao Du, Zhao Yang, Yujie Zhou, Jiangmeng Li, Anyi Rao, Hao Sun, Zhiwu Lu, Ji-Rong Wen
Although artificial intelligence (AI) has made significant progress in understanding molecules in a wide range of fields, existing models generally acquire the single cognitive ability from the single molecular modality.
Ranked #7 on Molecule Captioning on ChEBI-20
2 code implementations • 16 Sep 2022 • Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, Farid Razzak, Ji-Rong Wen, Hui Xiong
To this end, we propose a methodology, specifically consistency and complementarity network (CoCoNet), which avails of strict global inter-view consistency and local cross-view complementarity preserving regularization to comprehensively learn representations from multiple views.
1 code implementation • 20 Oct 2022 • Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen
We show that the framework is model-agnostic, and a number of legal case matching models can be applied as the underlying models.
1 code implementation • 21 Oct 2022 • Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen
To develop effective and efficient graph similarity learning (GSL) models, a series of data-driven neural algorithms have been proposed in recent years.
1 code implementation • 21 Oct 2022 • Kun Zhou, Yeyun Gong, Xiao Liu, Wayne Xin Zhao, Yelong Shen, Anlei Dong, Jingwen Lu, Rangan Majumder, Ji-Rong Wen, Nan Duan, Weizhu Chen
Thus, we propose a simple ambiguous negatives sampling method, SimANS, which incorporates a new sampling probability distribution to sample more ambiguous negatives.
1 code implementation • 24 Oct 2022 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
However, NAR models usually generate texts of lower quality due to the absence of token dependency in the output text.
1 code implementation • 21 Nov 2022 • Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao
Some recent knowledge distillation based methods transfer knowledge from complex teacher models to shallow student models for accelerating the online model inference.
2 code implementations • 27 Nov 2022 • Wayne Xin Zhao, Jing Liu, Ruiyang Ren, Ji-Rong Wen
With powerful PLMs, we can effectively learn the representations of queries and texts in the latent representation space, and further construct the semantic matching function between the dense vectors for relevance modeling.
1 code implementation • 28 Nov 2022 • Lanling Xu, Zhen Tian, Gaowei Zhang, Lei Wang, Junjie Zhang, Bowen Zheng, YiFan Li, Yupeng Hou, Xingyu Pan, Yushuo Chen, Wayne Xin Zhao, Xu Chen, Ji-Rong Wen
In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole.
1 code implementation • 30 Nov 2022 • Jing Yao, Zheng Liu, Junhan Yang, Zhicheng Dou, Xing Xie, Ji-Rong Wen
In the first stage, a lightweight CNN-based ad-hod neighbor selector is deployed to filter useful neighbors for the matching task with a small computation cost.
1 code implementation • 2 Dec 2022 • Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
Multi-hop Question Answering over Knowledge Graph~(KGQA) aims to find the answer entities that are multiple hops away from the topic entities mentioned in a natural language question on a large-scale Knowledge Graph (KG).
1 code implementation • 15 Dec 2022 • Kun Zhou, Xiao Liu, Yeyun Gong, Wayne Xin Zhao, Daxin Jiang, Nan Duan, Ji-Rong Wen
Pre-trained Transformers (\eg BERT) have been commonly used in existing dense retrieval methods for parameter initialization, and recent studies are exploring more effective pre-training tasks for further improving the quality of dense vectors.
1 code implementation • 15 Dec 2022 • Hangyu Guo, Kun Zhou, Wayne Xin Zhao, Qinyu Zhang, Ji-Rong Wen
Although pre-trained language models~(PLMs) have shown impressive performance by text-only self-supervised training, they are found lack of visual semantics or commonsense.
1 code implementation • 26 Dec 2022 • Tianyi Tang, Junyi Li, Zhipeng Chen, Yiwen Hu, Zhuohao Yu, Wenxun Dai, Zican Dong, Xiaoxue Cheng, Yuhao Wang, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
To facilitate research on text generation, this paper presents a comprehensive and unified library, TextBox 2. 0, focusing on the use of pre-trained language models (PLMs).
Ranked #1 on Abstractive Text Summarization on CNN/Daily Mail
no code implementations • 1 Mar 2023 • Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Ji-Rong Wen
To alleviate the above problems, we propose to build an explainable recommendation dataset with multi-aspect real user labeled ground truths.
1 code implementation • 12 Mar 2023 • YiFan Li, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
In this survey, we review the recent progress in diffusion models for NAR text generation.
1 code implementation • 15 Mar 2023 • Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, Ji-Rong Wen
According to the graph, two complementary propensity scores are estimated from the views of item and user, respectively, based on the same set of user feedback data.
no code implementations • 27 Mar 2023 • Peiyu Liu, Ze-Feng Gao, Yushuo Chen, Wayne Xin Zhao, Ji-Rong Wen
Based on such a decomposition, our architecture shares the central tensor across all layers for reducing the model size and meanwhile keeps layer-specific auxiliary tensors (also using adapters) for enhancing the adaptation flexibility.
5 code implementations • 31 Mar 2023 • Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, YiFan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, Ji-Rong Wen
To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size.
1 code implementation • 10 Apr 2023 • Hongjing Qian, Yutao Zhu, Zhicheng Dou, Haoqi Gu, Xinyu Zhang, Zheng Liu, Ruofei Lai, Zhao Cao, Jian-Yun Nie, Ji-Rong Wen
In this paper, we introduce a new NLP task -- generating short factual articles with references for queries by mining supporting evidence from the Web.
1 code implementation • 21 Apr 2023 • Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen, Zhao Cao
EulerNet converts the exponential powers of feature interactions into simple linear combinations of the modulus and phase of the complex features, making it possible to adaptively learn the high-order feature interactions in an efficient way.
no code implementations • 25 Apr 2023 • Junyi Li, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
In this way, conditional text generation can be cast as a glyph image generation task, and it is then natural to apply continuous diffusion models to discrete texts.
no code implementations • 6 May 2023 • Kun Zhou, YiFan Li, Wayne Xin Zhao, Ji-Rong Wen
To solve it, we propose Diffusion-NAT, which introduces discrete diffusion models~(DDM) into NAR text-to-text generation and integrates BART to improve the performance.
no code implementations • 11 May 2023 • Junjie Zhang, Ruobing Xie, Yupeng Hou, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen
Inspired by the recent progress on large language models (LLMs), we take a different approach to developing the recommendation models, considering recommendation as instruction following by LLMs.
1 code implementation • 16 May 2023 • Jinhao Jiang, Kun Zhou, Zican Dong, Keming Ye, Wayne Xin Zhao, Ji-Rong Wen
Specially, we propose an \emph{invoking-linearization-generation} procedure to support LLMs in reasoning on the structured data with the help of the external interfaces.
2 code implementations • 17 May 2023 • YiFan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Wayne Xin Zhao, Ji-Rong Wen
Despite the promising progress on LVLMs, we find that LVLMs suffer from the hallucination problem, i. e. they tend to generate objects that are inconsistent with the target images in the descriptions.
no code implementations • 18 May 2023 • Ruiyang Ren, Wayne Xin Zhao, Jing Liu, Hua Wu, Ji-Rong Wen, Haifeng Wang
Recently, model-based retrieval has emerged as a new paradigm in text retrieval that discards the index in the traditional retrieval model and instead memorizes the candidate corpora using model parameters.
1 code implementation • 18 May 2023 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jingyuan Wang, Jian-Yun Nie, Ji-Rong Wen
In order to further improve the capacity of LLMs for knowledge-intensive tasks, we consider augmenting LLMs with the large-scale web using search engine.
1 code implementation • 18 May 2023 • Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang song, Kun Gai, Ji-Rong Wen
In our paper, we propose a Search-Enhanced framework for the Sequential Recommendation (SESRec) that leverages users' search interests for recommendation, by disentangling similar and dissimilar representations within S&R behaviors.
2 code implementations • 19 May 2023 • Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i. e., content that conflicts with the source or cannot be verified by the factual knowledge.
1 code implementation • 22 May 2023 • Xiaolei Wang, Xinyu Tang, Wayne Xin Zhao, Jingyuan Wang, Ji-Rong Wen
The recent success of large language models (LLMs) has shown great potential to develop more powerful conversational recommender systems (CRSs), which rely on natural language conversations to satisfy user needs.
1 code implementation • 23 May 2023 • Zhipeng Chen, Kun Zhou, Beichen Zhang, Zheng Gong, Wayne Xin Zhao, Ji-Rong Wen
Although large language models (LLMs) have achieved excellent performance in a variety of evaluation benchmarks, they still struggle in complex reasoning tasks which require specific knowledge and multi-hop reasoning.
1 code implementation • 26 May 2023 • Yifan Du, Junyi Li, Tianyi Tang, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we propose a novel language model guided captioning approach, LAMOC, for knowledge-based visual question answering (VQA).
1 code implementation • 26 May 2023 • Tianyi Tang, Yushuo Chen, Yifan Du, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen
People often imagine relevant scenes to aid in the writing process.
1 code implementation • NeurIPS 2023 • Beichen Zhang, Kun Zhou, Xilin Wei, Wayne Xin Zhao, Jing Sha, Shijin Wang, Ji-Rong Wen
Based on this finding, we propose a new approach that can deliberate the reasoning steps with tool interfaces, namely \textbf{DELI}.
1 code implementation • 5 Jun 2023 • Lei Wang, Jingsen Zhang, Hao Yang, ZhiYuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Ruihua Song, Wayne Xin Zhao, Jun Xu, Zhicheng Dou, Jun Wang, Ji-Rong Wen
Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism of human decision process.
1 code implementation • 5 Jun 2023 • Xiaolei Wang, Kun Zhou, Xinyu Tang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen
To develop our approach, we characterize user preference and organize the conversation flow by the entities involved in the dialogue, and design a multi-stage recommendation dialogue simulator based on a conversation flow language model.
1 code implementation • 8 Jun 2023 • Jiongnan Liu, Jiajie Jin, Zihan Wang, Jiehan Cheng, Zhicheng Dou, Ji-Rong Wen
To support research in this area and facilitate the development of retrieval-augmented LLM systems, we develop RETA-LLM, a {RET}reival-{A}ugmented LLM toolkit.
no code implementations • 19 Jun 2023 • Wayne Xin Zhao, Kun Zhou, Beichen Zhang, Zheng Gong, Zhipeng Chen, Yuanhang Zhou, Ji-Rong Wen, Jing Sha, Shijin Wang, Cong Liu, Guoping Hu
Specially, we construct a Mixture-of-Experts~(MoE) architecture for modeling mathematical text, so as to capture the common mathematical knowledge across tasks.
1 code implementation • 2 Jul 2023 • Quan Tu, Shen Gao, Xiaolong Wu, Zhao Cao, Ji-Rong Wen, Rui Yan
Conversational search has been regarded as the next-generation search paradigm.
1 code implementation • 16 Jul 2023 • Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen
Different from previous studies focused on overall performance, this work aims to investigate the impact of quantization on \emph{emergent abilities}, which are important characteristics that distinguish LLMs from small language models.
no code implementations • 19 Jul 2023 • Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs.
1 code implementation • 20 Jul 2023 • Ruiyang Ren, Yuhao Wang, Yingqi Qu, Wayne Xin Zhao, Jing Liu, Hao Tian, Hua Wu, Ji-Rong Wen, Haifeng Wang
In this study, we present an initial analysis of the factual knowledge boundaries of LLMs and how retrieval augmentation affects LLMs on open-domain QA.
1 code implementation • 21 Jul 2023 • Zhipeng Zhao, Kun Zhou, Xiaolei Wang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen
Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations.
1 code implementation • 2 Aug 2023 • Jiexin Wang, Yujie Zhou, Wenwen Qiang, Ying Ba, Bing Su, Ji-Rong Wen
Human motion prediction (HMP) has emerged as a popular research topic due to its diverse applications, but it remains a challenging task due to the stochastic and aperiodic nature of future poses.
1 code implementation • 3 Aug 2023 • Zhao Yang, Bing Su, Ji-Rong Wen
Firstly, they cannot directly generate coherent motions and require additional operations such as interpolation to process the generated actions.
1 code implementation • 10 Aug 2023 • Zezhong Lv, Bing Su, Ji-Rong Wen
Finally, by suppressing the unimodal effect of masked query, we can rectify the reconstructions of video proposals to perform reasonable contrastive learning.
1 code implementation • 11 Aug 2023 • Chen Xu, Xiaopeng Ye, Jun Xu, Xiao Zhang, Weiran Shen, Ji-Rong Wen
RFL means that recommender system can only receive feedback on exposed items from users and update recommender models incrementally based on this feedback.
1 code implementation • 14 Aug 2023 • Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Haonan Chen, Zhicheng Dou, Ji-Rong Wen
This evolution requires a combination of both traditional methods (such as term-based sparse retrieval methods with rapid response) and modern neural architectures (such as language models with powerful language understanding capacity).
1 code implementation • 16 Aug 2023 • Haiyuan Zhao, Lei Zhang, Jun Xu, Guohao Cai, Zhenhua Dong, Ji-Rong Wen
In the video recommendation, watch time is commonly adopted as an indicator of user interest.
2 code implementations • 22 Aug 2023 • Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, ZhiYuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, Ji-Rong Wen
In this paper, we present a comprehensive survey of these studies, delivering a systematic review of the field of LLM-based autonomous agents from a holistic perspective.
no code implementations • 30 Aug 2023 • Hongjin Qian, Zhicheng Dou, Jiejun Tan, Haonan Chen, Haoqi Gu, Ruofei Lai, Xinyu Zhang, Zhao Cao, Ji-Rong Wen
Previous methods use external knowledge as references for text generation to enhance factuality but often struggle with the knowledge mix-up(e. g., entity mismatch) of irrelevant references.
1 code implementation • 23 Sep 2023 • Zican Dong, Tianyi Tang, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen
Recently, multiple studies have committed to extending the context length and enhancing the long text modeling capabilities of LLMs.
no code implementations • 13 Oct 2023 • Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian McAuley, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen
The optimized agents can also propagate their preferences to other agents in subsequent interactions, implicitly capturing the collaborative filtering idea.
1 code implementation • 28 Oct 2023 • Hongda Sun, Weikai Xu, Wei Liu, Jian Luan, Bin Wang, Shuo Shang, Ji-Rong Wen, Rui Yan
To address these challenges, we propose DetermLR, a novel reasoning framework that formulates the reasoning process as a transformational journey from indeterminate premises to determinate ones.
1 code implementation • 2 Nov 2023 • Yifan Du, Hangyu Guo, Kun Zhou, Wayne Xin Zhao, Jinpeng Wang, Chuyuan Wang, Mingchen Cai, Ruihua Song, Ji-Rong Wen
By conducting a comprehensive empirical study, we find that instructions focused on complex visual reasoning tasks are particularly effective in improving the performance of MLLMs on evaluation benchmarks.
no code implementations • 3 Nov 2023 • Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen, Wayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong Wen, Jiawei Han
Large language models~(LLMs) have greatly advanced the frontiers of artificial intelligence, attaining remarkable improvement in model capacity.
1 code implementation • 7 Nov 2023 • Geyang Guo, Ranchi Zhao, Tianyi Tang, Wayne Xin Zhao, Ji-Rong Wen
Alignment with human preference is a desired property of large language models (LLMs).
1 code implementation • 8 Nov 2023 • Ze-Feng Gao, Shuai Qu, Bocheng Zeng, Yang Liu, Ji-Rong Wen, Hao Sun, Peng-Jie Guo, Zhong-Yi Lu
Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism.
1 code implementation • 13 Nov 2023 • Ang Lv, Kaiyi Zhang, Shufang Xie, Quan Tu, Yuhan Chen, Ji-Rong Wen, Rui Yan
Recent studies have highlighted a phenomenon in large language models (LLMs) known as "the reversal curse," in which the order of knowledge entities in the training data biases the models' comprehension.
1 code implementation • 15 Nov 2023 • Bowen Zheng, Yupeng Hou, Hongyu Lu, Yu Chen, Wayne Xin Zhao, Ming Chen, Ji-Rong Wen
To address this challenge, in this paper, we propose a new LLM-based recommendation model called LC-Rec, which can better integrate language and collaborative semantics for recommender systems.
no code implementations • 19 Nov 2023 • Gaowei Zhang, Yupeng Hou, Hongyu Lu, Yu Chen, Wayne Xin Zhao, Ji-Rong Wen
We find that scaling up the model size can greatly boost the performance on these challenging tasks, which again verifies the benefits of large recommendation models.
1 code implementation • 27 Nov 2023 • Zhen Tian, Changwang Zhang, Wayne Xin Zhao, Xin Zhao, Ji-Rong Wen, Zhao Cao
To address the above issue, we propose the Universal Feature Interaction Network (UFIN) approach for CTR prediction.
1 code implementation • 17 Dec 2023 • Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation.
no code implementations • 30 Dec 2023 • Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen
To better perform reasoning on KG, recent work typically adopts a pre-trained language model~(PLM) to model the question, and a graph neural network~(GNN) based module to perform multi-hop reasoning on the KG.
no code implementations • 1 Jan 2024 • Wenqi Sun, Ruobing Xie, Junjie Zhang, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen
Pre-trained recommendation models (PRMs) have attracted widespread attention recently.
1 code implementation • 6 Jan 2024 • Junyi Li, Jie Chen, Ruiyang Ren, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, Ji-Rong Wen
To tackle the LLM hallucination, three key questions should be well studied: how to detect hallucinations (detection), why do LLMs hallucinate (source), and what can be done to mitigate them (mitigation).
no code implementations • 10 Jan 2024 • Lanling Xu, Junjie Zhang, Bingqian Li, Jinpeng Wang, Mingchen Cai, Wayne Xin Zhao, Ji-Rong Wen
As for the use of LLMs as recommenders, we analyze the impact of public availability, tuning strategies, model architecture, parameter scale, and context length on recommendation results based on the classification of LLMs.
1 code implementation • 11 Jan 2024 • Zhipeng Chen, Kun Zhou, Wayne Xin Zhao, Junchen Wan, Fuzheng Zhang, Di Zhang, Ji-Rong Wen
To address it, we propose a new RL method named \textbf{RLMEC} that incorporates a generative model as the reward model, which is trained by the erroneous solution rewriting task under the minimum editing constraint, and can produce token-level rewards for RL training.
1 code implementation • 12 Jan 2024 • Yutao Zhu, Peitian Zhang, Chenghao Zhang, Yifei Chen, Binyu Xie, Zhicheng Dou, Zheng Liu, Ji-Rong Wen
Despite this, their application to information retrieval (IR) tasks is still challenging due to the infrequent occurrence of many IR-specific concepts in natural language.
no code implementations • 17 Feb 2024 • Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Yang song, Chen Zhu, HengShu Zhu, Ji-Rong Wen
To guarantee the effectiveness, we leverage program language to formulate the multi-hop reasoning process over the KG, and synthesize a code-based instruction dataset to fine-tune the base LLM.
1 code implementation • 19 Feb 2024 • Jiejun Tan, Zhicheng Dou, Yutao Zhu, Peidong Guo, Kun Fang, Ji-Rong Wen
The integration of large language models (LLMs) and search engines represents a significant evolution in knowledge acquisition methodologies.
1 code implementation • 20 Feb 2024 • Xueyang Feng, Zhi-Yuan Chen, Yujia Qin, Yankai Lin, Xu Chen, Zhiyuan Liu, Ji-Rong Wen
We construct a human-agent collaboration dataset to train this policy model in an offline reinforcement learning environment.
1 code implementation • 22 Feb 2024 • Zhaoheng Huang, Zhicheng Dou, Yutao Zhu, Ji-Rong Wen
To address these challenges, we categorize four available fact sources: human-written evidence, reference documents, search engine results, and LLM knowledge, along with five text generation tasks containing six representative datasets.
no code implementations • 26 Feb 2024 • Tianyi Tang, Wenyang Luo, Haoyang Huang, Dongdong Zhang, Xiaolei Wang, Xin Zhao, Furu Wei, Ji-Rong Wen
Large language models (LLMs) demonstrate remarkable multilingual capabilities without being pre-trained on specially curated multilingual parallel corpora.
1 code implementation • 27 Feb 2024 • Yuhao Wang, Ruiyang Ren, Junyi Li, Wayne Xin Zhao, Jing Liu, Ji-Rong Wen
By combining the improvements in both architecture and training, our proposed REAR can better utilize external knowledge by effectively perceiving the relevance of retrieved documents.
no code implementations • 27 Feb 2024 • Ruiyang Ren, Peng Qiu, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Hua Wu, Ji-Rong Wen, Haifeng Wang
Due to the excellent capacities of large language models (LLMs), it becomes feasible to develop LLM-based agents for reliable user simulation.
1 code implementation • 27 Feb 2024 • Xinyu Tang, Xiaolei Wang, Wayne Xin Zhao, Siyuan Lu, Yaliang Li, Ji-Rong Wen
Focused on the two aspects, we borrow the theoretical framework and learning methods from gradient-based optimization to design improved strategies for LLM-based prompt optimizers.
1 code implementation • 4 Mar 2024 • Changyu Chen, Xiting Wang, Ting-En Lin, Ang Lv, Yuchuan Wu, Xin Gao, Ji-Rong Wen, Rui Yan, Yongbin Li
In reasoning tasks, even a minor error can cascade into inaccurate results, leading to suboptimal performance of large language models in such domains.
no code implementations • 13 Mar 2024 • Jia-Nan Li, Quan Tu, Cunli Mao, Zhengtao Yu, Ji-Rong Wen, Rui Yan
Accordingly, we introduce StreamingDialogue, which compresses long dialogue history into conv-attn sinks with minimal losses, and thus reduces computational complexity quadratically with the number of sinks (i. e., the number of utterances).
no code implementations • 14 Mar 2024 • Zikang Liu, Kun Zhou, Wayne Xin Zhao, Dawei Gao, Yaliang Li, Ji-Rong Wen
To investigate this issue, we conduct a series of empirical studies, which reveal a significant redundancy within the visual instruction datasets, and show that greatly reducing the amount of several instruction dataset even do not affect the performance.
1 code implementation • 14 Mar 2024 • YiFan Li, Hangyu Guo, Kun Zhou, Wayne Xin Zhao, Ji-Rong Wen
In this paper, we study the harmlessness alignment problem of multimodal large language models (MLLMs).
1 code implementation • 20 Mar 2024 • Bowen Zheng, Zihan Lin, Enze Liu, Chen Yang, Enyang Bai, Cheng Ling, Wayne Xin Zhao, Ji-Rong Wen
Meanwhile, we leverage the LLM recommender as a supplemental component (discarded in deployment) to better capture underlying user preferences from heterogeneous interaction behaviors.
no code implementations • 20 Mar 2024 • Qi Liu, Gang Guo, Jiaxin Mao, Zhicheng Dou, Ji-Rong Wen, Hao Jiang, Xinyu Zhang, Zhao Cao
Based on these findings, we then propose several simple document pruning methods to reduce the storage overhead and compare the effectiveness of different pruning methods on different late-interaction models.
1 code implementation • 21 Mar 2024 • Xiaoxue Cheng, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen
In response to this challenge, we present an empirical investigation of CoT prompting and introduce CoTGenius, a novel framework designed for the automatic generation of superior CoT prompts.
no code implementations • 22 Mar 2024 • Xiaoqing Zhang, Xiuying Chen, Shen Gao, Shuqi Li, Xin Gao, Ji-Rong Wen, Rui Yan
Given the user query, the information-seeking dialogue systems first retrieve a subset of response candidates, then further select the best response from the candidate set through re-ranking.
1 code implementation • 26 Mar 2024 • Zhen Tian, Wayne Xin Zhao, Changwang Zhang, Xin Zhao, Zhongrui Ma, Ji-Rong Wen
The core of transformer architecture lies in the self-attention mechanism, which computes the pairwise attention scores in a sequence.