1 code implementation • EMNLP 2021 • Dan Liu, Mengge Du, Xiaoxi Li, Ya Li, Enhong Chen
This paper proposes a novel architecture, Cross Attention Augmented Transducer (CAAT), for simultaneous translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • 5 Feb 2025 • Cheng He, Xu Huang, Gangwei Jiang, Zhaoyi Li, Defu Lian, Hong Xie, Enhong Chen, Xijie Liang, Zengrong Zheng
Universal knowledge representation is a central problem for multivariate time series(MTS) foundation models and yet remains open.
1 code implementation • 5 Feb 2025 • Jiaqing Zhang, Mingjia Yin, Hao Wang, Yawen Li, Yuyang Ye, Xingyu Lou, Junping Du, Enhong Chen
In the era of data-centric AI, the focus of recommender systems has shifted from model-centric innovations to data-centric approaches.
1 code implementation • 15 Jan 2025 • Jin Chen, Jin Zhang, Xu Huang, Yi Yang, Defu Lian, Enhong Chen
The softmax function is a cornerstone of multi-class classification, integral to a wide range of machine learning applications, from large-scale retrieval and ranking models to advanced large language models.
1 code implementation • 30 Dec 2024 • Yitong Zhou, Mingyue Cheng, Qingyang Mao, Qi Liu, Feiyang Xu, Xin Li, Enhong Chen
Pre-trained foundation models have recently significantly progressed in structured table understanding and reasoning.
1 code implementation • 24 Dec 2024 • Derong Xu, Xinhang Li, Ziheng Zhang, Zhenxi Lin, Zhihong Zhu, Zhi Zheng, Xian Wu, Xiangyu Zhao, Tong Xu, Enhong Chen
The Amar framework comprises two key sub-components: 1) a self-alignment module that aligns commonalities among entities, relations, and subgraphs to enhance retrieved text, thereby reducing noise interference; 2) a relevance gating module that employs a soft gate to learn the relevance score between question and multi-aspect retrieved data, to determine which information should be used to enhance LLMs' output, or even filtered altogether.
1 code implementation • 12 Dec 2024 • Liyang He, Yuren Zhang, Rui Li, Zhenya Huang, Runze Wu, Enhong Chen
The NHL framework introduces a novel mechanism to simultaneously generate hash codes of varying lengths in a nested manner.
1 code implementation • 1 Dec 2024 • Wei Guo, Hao Wang, Luankang Zhang, Jin Yao Chin, Zhongzhou Liu, Kai Cheng, Qiushi Pan, Yi Quan Lee, Wanqi Xue, Tingjia Shen, Kenan Song, Kefan Wang, Wenjia Xie, Yuyang Ye, Huifeng Guo, Yong liu, Defu Lian, Ruiming Tang, Enhong Chen
In this paper, we aim to enhance the understanding of scaling laws by conducting comprehensive evaluations of large recommendation models.
no code implementations • 30 Nov 2024 • Tingjia Shen, Hao Wang, Chuhan Wu, Jin Yao Chin, Wei Guo, Yong liu, Huifeng Guo, Defu Lian, Ruiming Tang, Enhong Chen
In response, we introduce the Performance Law for SR models, which aims to theoretically investigate and model the relationship between model performance and data quality.
1 code implementation • 29 Nov 2024 • Shukang Yin, Chaoyou Fu, Sirui Zhao, Yunhang Shen, Chunjiang Ge, Yan Yang, Zuwei Long, Yuhan Dai, Tong Xu, Xing Sun, Ran He, Caifeng Shan, Enhong Chen
In this work, our study of these approaches harvests an effective data augmentation method.
1 code implementation • 24 Nov 2024 • Jiahao Wang, Mingyue Cheng, Qingyang Mao, Qi Liu, Feiyang Xu, Xin Li, Enhong Chen
Despite their effectiveness, we reveal that these methods conceal three inherent bottlenecks: (1) they struggle to encode temporal and channel-specific information in a lossless manner, both of which are critical components of multivariate time series; (2) it is much difficult to align the learned representation space with the semantic space of the LLMs; (3) they require task-specific retraining, which is both computationally expensive and labor-intensive.
no code implementations • 24 Nov 2024 • Suyuan Huang, Chao Zhang, Yuanyuan Wu, Haoxin Zhang, YuAn Wang, Maolin Wang, Shaosheng Cao, Tong Xu, Xiangyu Zhao, Zengchang Qin, Yan Gao, Yunhan Bai, Jun Fan, Yao Hu, Enhong Chen
However, scaling up retrieval models significantly increases online query latency.
2 code implementations • 22 Nov 2024 • Xiang Xu, Hao Wang, Wei Guo, Luankang Zhang, Wanshan Yang, Runlong Yu, Yong liu, Defu Lian, Enhong Chen
Recent advancements have shown that modeling rich user behaviors can significantly improve the performance of CTR prediction.
no code implementations • 31 Oct 2024 • Wenjia Xie, Hao Wang, Luankang Zhang, Rui Zhou, Defu Lian, Enhong Chen
Sequential recommendation (SR) aims to predict items that users may be interested in based on their historical behavior sequences.
no code implementations • 30 Oct 2024 • Zhiding Liu, Jiqian Yang, Qingyang Mao, Yuze Zhao, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen
To this end, we propose DisenTS, a tailored framework for modeling disentangled channel evolving patterns in general multivariate time series forecasting.
no code implementations • 21 Oct 2024 • Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
In this paper, we address these hallucination issues in the context of Medical Information Extraction (MIE) tasks by introducing ALternate Contrastive Decoding (ALCD).
1 code implementation • 10 Oct 2024 • Xukai Liu, Ye Liu, Kai Zhang, Kehang Wang, Qi Liu, Enhong Chen
Entity Linking (EL) is the process of associating ambiguous textual mentions to specific entities in a knowledge base.
1 code implementation • 9 Oct 2024 • Hao Zhang, Mingyue Cheng, Qi Liu, Yucong Luo, Rui Li, Enhong Chen
Learning recommender systems with multi-class optimization objective is a prevalent setting in recommendation.
1 code implementation • 8 Oct 2024 • Junxiong Tong, Mingjia Yin, Hao Wang, Qiushi Pan, Defu Lian, Enhong Chen
Cross-domain Recommendation systems leverage multi-domain user interactions to improve performance, especially in sparse data or new user scenarios.
3 code implementations • 8 Oct 2024 • Daoyu Wang, Mingyue Cheng, Zhiding Liu, Qi Liu, Enhong Chen
Self-supervised learning has become a popular and effective approach for enhancing time series forecasting, enabling models to learn universal representations from unlabeled data.
no code implementations • 1 Oct 2024 • Shiwei Wu, Chen Zhang, Yan Gao, Qimeng Wang, Tong Xu, Yao Hu, Enhong Chen
Instructional documents are rich sources of knowledge for completing various tasks, yet their unique challenges in conversational question answering (CQA) have not been thoroughly explored.
no code implementations • 23 Sep 2024 • Li Li, Mingyue Cheng, Zhiding Liu, Hao Zhang, Qi Liu, Enhong Chen
The algorithm operates in two stages: in the first stage, we fine-tune the pre-trained language model on the recommendation dataset to transfer the pre-trained knowledge to the recommendation task; in the second stage, we distill the trained language model to transfer the learned knowledge to a lightweight model.
1 code implementation • 21 Sep 2024 • Yuqing Huang, Rongyang Zhang, Xuesong He, Xuyang Zhi, Hao Wang, Xin Li, Feiyang Xu, Deguang Liu, Huadong Liang, Yi Li, Jian Cui, Zimu Liu, Shijin Wang, Guoping Hu, Guiquan Liu, Qi Liu, Defu Lian, Enhong Chen
To this end, we propose \textbf{\textit{ChemEval}}, which provides a comprehensive assessment of the capabilities of LLMs across a wide range of chemical domain tasks.
no code implementations • 14 Sep 2024 • Yuanjie Lyu, Tong Xu, Zihan Niu, Bo Peng, Jing Ke, Enhong Chen
Correspondingly, in the global stage, we strengthen the connections between associated events using an inferential knowledge graph, and design an event-aware prefix that directs the model to focus on associated events rather than all preceding clips, resulting in accurate event attribution.
1 code implementation • 9 Sep 2024 • Jie Ouyang, Yucong Luo, Mingyue Cheng, Daoyu Wang, Shuo Yu, Qi Liu, Enhong Chen
This paper presents the solution of our team APEX in the Meta KDD CUP 2024: CRAG Comprehensive RAG Benchmark Challenge.
2 code implementations • 3 Sep 2024 • Shuo Yu, Mingyue Cheng, Jiqian Yang, Jie Ouyang, Yucong Luo, Chenyi Lei, Qi Liu, Enhong Chen
Retrieval-augmented generation (RAG) is increasingly recognized as an effective approach for mitigating the hallucination of large language models (LLMs) through the integration of external knowledge.
no code implementations • 2 Sep 2024 • Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen
Function calling significantly extends the application boundary of large language models, where high-quality and diverse training data is critical for unlocking this capability.
no code implementations • 30 Aug 2024 • Wenjia Xie, Rui Zhou, Hao Wang, Tingjia Shen, Enhong Chen
Sequential recommendation has attracted increasing attention due to its ability to accurately capture the dynamic changes in user interests.
no code implementations • 29 Aug 2024 • Shiwei Wu, Joya Chen, Kevin Qinghong Lin, Qimeng Wang, Yan Gao, Qianli Xu, Tong Xu, Yao Hu, Enhong Chen, Mike Zheng Shou
Our method, VideoLLM-MoD, is inspired by mixture-of-depths LLMs and addresses the challenge of numerous vision tokens in long-term or streaming video.
no code implementations • 21 Aug 2024 • Hao Wang, Yongqiang Han, Kefan Wang, Kai Cheng, Zhen Wang, Wei Guo, Yong liu, Defu Lian, Enhong Chen
Its objective is to extract knowledge from extensive pre-training data and fine-tune the model for downstream tasks.
1 code implementation • 21 Aug 2024 • Ze Liu, Jin Zhang, Chao Feng, Defu Lian, Jie Wang, Enhong Chen
Although advancements in deep learning have significantly enhanced the recommendation accuracy of deep recommendation models, these methods still suffer from low recommendation efficiency.
no code implementations • 20 Aug 2024 • Hong Xie, Mingze Zhong, Defu Lian, Zhen Wang, Enhong Chen
We also study the speed of convergence numerically and reveal trade-offs in selecting rating aggregation rules and review selection mechanisms.
no code implementations • 20 Aug 2024 • Hong Xie, Jinyu Mo, Defu Lian, Jie Wang, Enhong Chen
We also design an iterative distributed algorithm for players to commit to an optimal arm pulling profile with a constant number of rounds in expectation.
1 code implementation • 6 Aug 2024 • Yanghai Zhang, Ye Liu, Shiwei Wu, Kai Zhang, Xukai Liu, Qi Liu, Enhong Chen
The rapid increase in multimedia data has spurred advancements in Multimodal Summarization with Multimodal Output (MSMO), which aims to produce a multimodal summary that integrates both text and relevant images.
no code implementations • 25 Jul 2024 • Haoyu Tang, Ye Liu, Xukai Liu, Kai Zhang, Yanghai Zhang, Qi Liu, Enhong Chen
Recent advancements in machine learning, particularly in Natural Language Processing (NLP), have led to the development of sophisticated models trained on extensive datasets, yet raising concerns about the potential leakage of sensitive information.
no code implementations • 12 Jul 2024 • Ye Liu, Jiajun Zhu, Kai Zhang, Haoyu Tang, Yanghai Zhang, Xukai Liu, Qi Liu, Enhong Chen
To address these shortcomings, we propose a Dual-perspective Augmented Fake News Detection (DAFND) model, designed to enhance LLMs from both inside and outside perspectives.
1 code implementation • 12 Jul 2024 • Ye Liu, Kai Zhang, Aoran Gan, Linan Yue, Feng Hu, Qi Liu, Enhong Chen
Specifically, DSARE innovatively injects the prior knowledge of LLMs into traditional RE models, and conversely enhances LLMs' task-specific aptitude for RE through relation extraction augmentation.
3 code implementations • 9 Jul 2024 • Mingjia Yin, Chuhan Wu, YuFei Wang, Hao Wang, Wei Guo, Yasheng Wang, Yong liu, Ruiming Tang, Defu Lian, Enhong Chen
Inspired by the information compression nature of LLMs, we uncover an ``entropy law'' that connects LLM performance with data compression ratio and first-epoch training loss, which reflect the information redundancy of a dataset and the mastery of inherent knowledge encoded in this dataset, respectively.
no code implementations • 7 Jul 2024 • Fei Wang, Weibo Gao, Qi Liu, Jiatong Li, Guanhao Zhao, Zheng Zhang, Zhenya Huang, Mengxiao Zhu, Shijin Wang, Wei Tong, Enhong Chen
Cognitive diagnosis has been developed for decades as an effective measurement tool to evaluate human cognitive status such as ability level and knowledge mastery.
no code implementations • 3 Jul 2024 • Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen
Recent advancements in graph learning have revolutionized the way to understand and analyze data with complex structures.
1 code implementation • 21 Jun 2024 • Yuanjie Lyu, Zihan Niu, Zheyong Xie, Chao Zhang, Tong Xu, Yang Wang, Enhong Chen
Despite the significant progress of large language models (LLMs) in various tasks, they often produce factual errors due to their limited internal knowledge.
no code implementations • 19 Jun 2024 • Xiangfeng Wang, Zaiyi Chen, Zheyong Xie, Tong Xu, Yongyi He, Enhong Chen
With the rising popularity of Transformer-based large language models (LLMs), reducing their high inference costs has become a significant research focus.
1 code implementation • 17 Jun 2024 • Fake Lin, Ziwei Zhao, Xi Zhu, Da Zhang, Shitian Shen, Xueying Li, Tong Xu, Suojuan Zhang, Enhong Chen
Last year has witnessed the re-flourishment of tag-aware recommender systems supported by the LLM-enriched tags.
no code implementations • 12 Jun 2024 • Shiwei Wu, Chao Zhang, Joya Chen, Tong Xu, Likang Wu, Yao Hu, Enhong Chen
People's social relationships are often manifested through their surroundings, with certain objects or interactions acting as symbols for specific relationships, e. g., wedding rings, roses, hugs, or holding hands.
1 code implementation • 5 Jun 2024 • Tingjia Shen, Hao Wang, Jiaqing Zhang, Sirui Zhao, Liangyue Li, Zulong Chen, Defu Lian, Enhong Chen
To this end, we propose a novel framework named URLLM, which aims to improve the CDSR performance by exploring the User Retrieval approach and domain grounding on LLM simultaneously.
1 code implementation • 3 Jun 2024 • Zhenya Huang, Yuting Ning, Longhu Qin, Shiwei Tong, Shangzi Xue, Tong Xiao, Xin Lin, Jiayu Liu, Qi Liu, Enhong Chen, Shijing Wang
We also provide a configurable pipeline to unify the data usage and model usage in standard ways, where users can customize their own needs.
1 code implementation • 31 May 2024 • Chaoyou Fu, Yuhan Dai, Yongdong Luo, Lei LI, Shuhuai Ren, Renrui Zhang, Zihan Wang, Chenyu Zhou, Yunhang Shen, Mengdan Zhang, Peixian Chen, Yanwei Li, Shaohui Lin, Sirui Zhao, Ke Li, Tong Xu, Xiawu Zheng, Enhong Chen, Rongrong Ji, Xing Sun
With Video-MME, we extensively evaluate various state-of-the-art MLLMs, including GPT-4 series and Gemini 1. 5 Pro, as well as open-source image models like InternVL-Chat-V1. 5 and video models like LLaVA-NeXT-Video.
no code implementations • 29 May 2024 • Runlong Yu, Qixiang Shao, Qi Liu, Huan Liu, Enhong Chen
We show that CELL can adaptively evolve into different models for different tasks and data, which enables practitioners to access off-the-shelf models.
1 code implementation • 28 May 2024 • Mingjia Yin, Hao Wang, Wei Guo, Yong liu, Suojuan Zhang, Sirui Zhao, Defu Lian, Enhong Chen
The sequential recommender (SR) system is a crucial component of modern recommender systems, as it aims to capture the evolving preferences of users.
1 code implementation • 27 May 2024 • Chao Zhang, Haoxin Zhang, Shiwei Wu, Di wu, Tong Xu, Xiangyu Zhao, Yan Gao, Yao Hu, Enhong Chen
While leveraging existing Multimodal Large Language Models (MLLMs) for such tasks is promising, challenges arise due to their delayed release compared to corresponding LLMs and the inefficiency in representation tasks.
no code implementations • 21 May 2024 • Mingjia Yin, Hao Wang, Wei Guo, Yong liu, Zhi Li, Sirui Zhao, Zhen Wang, Defu Lian, Enhong Chen
Cross-domain sequential recommendation (CDSR) aims to uncover and transfer users' sequential preferences across multiple recommendation domains.
no code implementations • 19 May 2024 • Fake Lin, Xi Zhu, Ziwei Zhao, Deqiang Huang, Yu Yu, Xueying Li, Zhi Zheng, Tong Xu, Enhong Chen
Recent years have witnessed the prosperity of knowledge graph based recommendation system (KGRS), which enriches the representation of users, items, and entities by structural knowledge with striking improvement.
no code implementations • 13 May 2024 • Ziwei Zhao, Fake Lin, Xi Zhu, Zhi Zheng, Tong Xu, Shitian Shen, Xueying Li, Zikai Yin, Enhong Chen
To bridge this gap, in this paper, we propose a novel framework, called DynLLM, to deal with the dynamic graph recommendation task with LLMs.
1 code implementation • 10 May 2024 • Tong Xiao, Jiayu Liu, Zhenya Huang, Jinze Wu, Jing Sha, Shijin Wang, Enhong Chen
Knowledge System controls an implicit reasoning process, which is responsible for providing diagram information and geometry knowledge according to a step-wise reasoning goal generated by Inference System.
no code implementations • 25 Apr 2024 • Zhihao Zhu, Ninglu Shao, Defu Lian, Chenwang Wu, Zheng Liu, Yi Yang, Enhong Chen
Large language models (LLMs) show early signs of artificial general intelligence but struggle with hallucinations.
no code implementations • 11 Apr 2024 • Xu Huang, Weiwen Liu, Xiaolong Chen, Xingmei Wang, Defu Lian, Yasheng Wang, Ruiming Tang, Enhong Chen
Concretely, WESE involves decoupling the exploration and exploitation process, employing a cost-effective weak agent to perform exploration tasks for global knowledge.
1 code implementation • 31 Mar 2024 • Qi Liu, Yan Zhuang, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen
Computerized Adaptive Testing (CAT) provides an efficient and tailored method for assessing the proficiency of examinees, by dynamically adjusting test questions based on their performance.
no code implementations • 30 Mar 2024 • Luankang Zhang, Hao Wang, Suojuan Zhang, Mingjia Yin, Yongqiang Han, Jiaqing Zhang, Defu Lian, Enhong Chen
To this end, we propose a Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation (AREIL).
no code implementations • 26 Mar 2024 • Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong liu, Defu Lian, Enhong Chen
In recommendation systems, users frequently engage in multiple types of behaviors, such as clicking, adding to a cart, and purchasing.
no code implementations • 21 Mar 2024 • Yuchen Cai, Ding Cao, Rongxi Guo, Yaqin Wen, Guiquan Liu, Enhong Chen
Prior research has typically tackled the issue of bias through a one-dimensional perspective, concentrating either on locating or mitigating it.
no code implementations • 21 Mar 2024 • Yuchen Cai, Ding Cao, Rongxi Guo, Yaqin Wen, Guiquan Liu, Enhong Chen
The results indicate that PSPEM can serve as an alternative to original prompts, supporting the model in effective editing.
1 code implementation • 13 Mar 2024 • Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen
Through this gateway, users have the opportunity to submit their questions, testing the models on a personalized and potentially broader range of capabilities.
1 code implementation • 12 Mar 2024 • Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li
It is also significant to model the \textit{semantic relatedness} reflected in content features, e. g., images and text.
1 code implementation • 10 Mar 2024 • Fei Wang, Haoyu Liu, Haoyang Bi, Xiangzhuang Shen, Renyu Zhu, Runze Wu, Minmin Lin, Tangjie Lv, Changjie Fan, Qi Liu, Zhenya Huang, Enhong Chen
In this paper, we introduce a substantial crowdsourcing annotation dataset collected from a real-world crowdsourcing platform.
1 code implementation • 10 Mar 2024 • Liyang He, Zhenya Huang, Jiayu Liu, Enhong Chen, Fei Wang, Jing Sha, Shijin Wang
In this paper, we propose an innovative Bit-mask Robust Contrastive knowledge Distillation (BRCD) method, specifically devised for the distillation of semantic hashing models.
no code implementations • 9 Mar 2024 • Fei Wang, Qi Liu, Enhong Chen, Chuanren Liu, Zhenya Huang, Jinze Wu, Shijin Wang
Specifically, based on the idea of estimating the posterior distributions of cognitive diagnosis model parameters, we first provide a unified objective function for mini-batch based optimization that can be more efficiently applied to a wide range of models and large datasets.
1 code implementation • 4 Mar 2024 • Derong Xu, Ziheng Zhang, Zhenxi Lin, Xian Wu, Zhihong Zhu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links.
no code implementations • 4 Mar 2024 • Chao Zhang, Shiwei Wu, Haoxin Zhang, Tong Xu, Yan Gao, Yao Hu, Di wu, Enhong Chen
Indeed, learning to generate hashtags/categories can potentially enhance note embeddings, both of which compress key note information into limited content.
1 code implementation • 28 Feb 2024 • Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Enhong Chen, Yefeng Zheng
To evaluate the editing impact on the behaviours of LLMs, we propose two model editing studies for medical domain: (1) editing factual knowledge for medical specialization and (2) editing the explanatory ability for complex knowledge.
no code implementations • 26 Feb 2024 • Hantao Yang, Xutong Liu, Zhiyong Wang, Hong Xie, John C. S. Lui, Defu Lian, Enhong Chen
We study the problem of federated contextual combinatorial cascading bandits, where $|\mathcal{U}|$ agents collaborate under the coordination of a central server to provide tailored recommendations to the $|\mathcal{U}|$ corresponding users.
no code implementations • 19 Feb 2024 • Yifei Cheng, Li Shen, Linli Xu, Xun Qian, Shiwei Wu, Yiming Zhou, Tie Zhang, DaCheng Tao, Enhong Chen
However, existing compression methods either perform only unidirectional compression in one iteration with higher communication cost, or bidirectional compression with slower convergence rate.
no code implementations • 15 Feb 2024 • Yuxuan Gu, Yi Jin, Ben Wang, Zhixiang Wei, Xiaoxiao Ma, Pengyang Ling, Haoxuan Wang, Huaian Chen, Enhong Chen
In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement against varying scenarios. Specifically, we embed a pre-trained generator to Retinex model to produce reflectance maps with enhanced detail and vividness, thereby recovering features degraded by low-light conditions. Taking one step further, we introduce a novel optimization strategy, which backpropagates the gradients to the input seeds rather than the parameters of the low-light enhancement model, thus intactly retaining the generative knowledge learned from natural images and achieving faster convergence speed.
no code implementations • 5 Feb 2024 • Xu Huang, Weiwen Liu, Xiaolong Chen, Xingmei Wang, Hao Wang, Defu Lian, Yasheng Wang, Ruiming Tang, Enhong Chen
As Large Language Models (LLMs) have shown significant intelligence, the progress to leverage LLMs as planning modules of autonomous agents has attracted more attention.
1 code implementation • 30 Jan 2024 • Yuanjie Lyu, Zhiyu Li, Simin Niu, Feiyu Xiong, Bo Tang, Wenjin Wang, Hao Wu, Huanyong Liu, Tong Xu, Enhong Chen
For each of these CRUD categories, we have developed comprehensive datasets to evaluate the performance of RAG systems.
1 code implementation • 23 Jan 2024 • Qingyang Wang, Chenwang Wu, Defu Lian, Enhong Chen
Consequently, we put forth a Game-based Co-training Attack (GCoAttack), which frames the proposed CoAttack and TCD as a game-theoretic process, thoroughly exploring CoAttack's attack potential in the cooperative training of attack and defense.
no code implementations • 18 Jan 2024 • Yichao Du, Zhirui Zhang, Linan Yue, Xu Huang, Yuqing Zhang, Tong Xu, Linli Xu, Enhong Chen
To protect privacy and meet legal regulations, federated learning (FL) has gained significant attention for training speech-to-text (S2T) systems, including automatic speech recognition (ASR) and speech translation (ST).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
1 code implementation • 29 Dec 2023 • Derong Xu, Wei Chen, Wenjun Peng, Chao Zhang, Tong Xu, Xiangyu Zhao, Xian Wu, Yefeng Zheng, Yang Wang, Enhong Chen
Information extraction (IE) aims to extract structural knowledge from plain natural language texts.
1 code implementation • 27 Dec 2023 • Lixiang Xu, Qingzhe Cui, Richang Hong, Wei Xu, Enhong Chen, Xin Yuan, Chenglong Li, Yuanyan Tang
The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.
1 code implementation • 25 Dec 2023 • Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Qi Liu, Enhong Chen
In this study, we propose LLMXRec, a simple yet effective two-stage explainable recommendation framework aimed at further boosting the explanation quality by employing LLMs.
no code implementations • 18 Dec 2023 • Zhihao Zhu, Rui Fan, Chenwang Wu, Yi Yang, Defu Lian, Enhong Chen
Some adversarial attacks have achieved model stealing attacks against recommender systems, to some extent, by collecting abundant training data of the target model (target data) or making a mass of queries.
no code implementations • 18 Dec 2023 • Zhihao Zhu, Chenwang Wu, Rui Fan, Yi Yang, Zhen Wang, Defu Lian, Enhong Chen
Recent research demonstrates that GNNs are vulnerable to the model stealing attack, a nefarious endeavor geared towards duplicating the target model via query permissions.
1 code implementation • 7 Nov 2023 • Wenjun Peng, Guiyang Li, Yue Jiang, Zilong Wang, Dan Ou, Xiaoyi Zeng, Derong Xu, Tong Xu, Enhong Chen
In the realm of e-commerce search, the significance of semantic matching cannot be overstated, as it directly impacts both user experience and company revenue.
1 code implementation • 6 Nov 2023 • Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong liu, Ruiming Tang, Defu Lian, Enhong Chen
To this end, we propose a graph-driven framework, named Adaptive and Personalized Graph Learning for Sequential Recommendation (APGL4SR), that incorporates adaptive and personalized global collaborative information into sequential recommendation systems.
no code implementations • 2 Nov 2023 • Keyu Ding, Yongcan Wang, Zihang Xu, Zhenzhen Jia, Shijin Wang, Cong Liu, Enhong Chen
The results demonstrate that we have achieved state-of-the-art performance for the first time in the Full-mode Key-sequence to Characters(FK2C) task.
1 code implementation • 1 Nov 2023 • Hao Zhang, Mingyue Cheng, Qi Liu, Zhiding Liu, Junzhe Jiang, Enhong Chen
Sequential recommender systems (SRS) have gained widespread popularity in recommendation due to their ability to effectively capture dynamic user preferences.
1 code implementation • 24 Oct 2023 • Shukang Yin, Chaoyou Fu, Sirui Zhao, Tong Xu, Hao Wang, Dianbo Sui, Yunhang Shen, Ke Li, Xing Sun, Enhong Chen
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with the image content.
1 code implementation • 21 Oct 2023 • Chuang Zhao, Hongke Zhao, HengShu Zhu, Zhenya Huang, Nan Feng, Enhong Chen, Hui Xiong
One prevalent solution is the bi-discriminator domain adversarial network, which strives to identify target domain samples outside the support of the source domain distribution and enforces their classification to be consistent on both discriminators.
1 code implementation • CIKM 2023 • Wei Chen, Lili Zhao, Pengfei Luo, Tong Xu, Yi Zheng, Enhong Chen
Great efforts have been made on this task with competitive performance, however, they usually treat the two subtasks, namely span detection and type classification, as mutually independent, and the integrity and correlation between subtasks have been largely ignored.
Ranked #4 on
Few-shot NER
on Few-NERD (INTER)
no code implementations • 9 Oct 2023 • Zheli Xiong, Defu Lian, Enhong Chen, Gang Chen, Xiaomin Cheng
To alleviate this problem, some researchers incorporate a prior OD matrix as a target in the regression to provide more structural constraints.
no code implementations • 20 Sep 2023 • Jie Wang, Hanzhu Chen, Qitan Lv, Zhihao Shi, Jiajun Chen, Huarui He, Hongtao Xie, Defu Lian, Enhong Chen, Feng Wu
This implies the great potential of the semantic correlations for the entity-independent inductive link prediction task.
no code implementations • 4 Sep 2023 • Jin Zhang, Defu Lian, Hong Xie, Yawen Li, Enhong Chen
Furthermore, we employ Bayesian meta-learning methods to effectively address the cold-start problem and derive theoretical regret bounds for our proposed method, ensuring a robust performance guarantee.
no code implementations • 15 Aug 2023 • Likang Wu, Junji Jiang, Hongke Zhao, Hao Wang, Defu Lian, Mengdi Zhang, Enhong Chen
However, the multi-faceted semantic orientation in the feature-semantic alignment has been neglected by previous work, i. e. the content of a node usually covers diverse topics that are relevant to the semantics of multiple labels.
2 code implementations • KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2023 • Runlong Yu, Xiang Xu, Yuyang Ye, Qi Liu, Enhong Chen
Inspired by natural evolution, we propose a general Cognitive EvoLutionary Search (CELS) framework, where cognitive ability refers to the malleability of organisms to orientate to the environment.
Ranked #3 on
Click-Through Rate Prediction
on Avazu
no code implementations • 31 Jul 2023 • Jin Chen, Zheng Liu, Xu Huang, Chenwang Wu, Qi Liu, Gangwei Jiang, Yuanhao Pu, Yuxuan Lei, Xiaolong Chen, Xingmei Wang, Defu Lian, Enhong Chen
The advent of large language models marks a revolutionary breakthrough in artificial intelligence.
1 code implementation • 19 Jul 2023 • Pengfei Luo, Tong Xu, Shiwei Wu, Chen Zhu, Linli Xu, Enhong Chen
Then, to derive the similarity matching score for each mention-entity pair, we device three interaction units to comprehensively explore the intra-modal interaction and inter-modal fusion among features of entities and mentions.
1 code implementation • 14 Jul 2023 • Qi Liu, Zheng Gong, Zhenya Huang, Chuanren Liu, HengShu Zhu, Zhi Li, Enhong Chen, Hui Xiong
Machine learning algorithms have become ubiquitous in a number of applications (e. g. image classification).
no code implementations • 11 Jul 2023 • Zheli Xiong, Defu Lian, Enhong Chen, Gang Chen, Xiaomin Cheng
To this end, this paper proposes an integrated method, which uses deep learning methods to infer the structure of OD sequence and uses structural constraints to guide traditional numerical optimization.
1 code implementation • 10 Jul 2023 • Likang Wu, Zhaopeng Qiu, Zhi Zheng, HengShu Zhu, Enhong Chen
This paper focuses on unveiling the capability of large language models in understanding behavior graphs and leveraging this understanding to enhance recommendations in online recruitment, including the promotion of out-of-distribution (OOD) application.
1 code implementation • 26 Jun 2023 • Chao Zhang, Shiwei Wu, Sirui Zhao, Tong Xu, Enhong Chen
In this paper, we present a solution for enhancing video alignment to improve multi-step inference.
1 code implementation • 23 Jun 2023 • Shukang Yin, Chaoyou Fu, Sirui Zhao, Ke Li, Xing Sun, Tong Xu, Enhong Chen
Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform multimodal tasks.
1 code implementation • 20 Jun 2023 • Zaixi Zhang, Jiaxian Yan, Yining Huang, Qi Liu, Enhong Chen, Mengdi Wang, Marinka Zitnik
Structure-based drug design (SBDD) leverages the three-dimensional geometry of proteins to identify potential drug candidates.
1 code implementation • 18 Jun 2023 • Yan Zhuang, Qi Liu, Yuting Ning, Weizhe Huang, Zachary A. Pardos, Patrick C. Kyllonen, Jiyun Zu, Qingyang Mao, Rui Lv, Zhenya Huang, Guanhao Zhao, Zheng Zhang, Shijin Wang, Enhong Chen
As AI systems continue to grow, particularly generative models like Large Language Models (LLMs), their rigorous evaluation is crucial for development and deployment.
1 code implementation • 15 Jun 2023 • Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang
Then, we propose a novel Relation of Relation Learning Network (R2-Net) for text classification, in which text classification and R2 classification are treated as optimization targets.
1 code implementation • 15 Jun 2023 • Shuangli Li, Jingbo Zhou, Ji Liu, Tong Xu, Enhong Chen, Hui Xiong
Specifically, we propose a solution to Trial with a graph learning scheme, which includes a spatially evolving graph neural network (SEENet) with two collaborative components: spatially evolving graph convolution module (SEConv) and spatially evolving self-supervised learning strategy (SE-SSL).
no code implementations • 14 Jun 2023 • Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen
Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.
2 code implementations • 31 May 2023 • Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, HengShu Zhu, Qi Liu, Hui Xiong, Enhong Chen
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS).
Ranked #1 on
on Amazon Review 2023
1 code implementation • 12 Apr 2023 • Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
Our extensive investigation reveals that the 2D topology and 3D geometry contain intrinsically complementary information in molecule design, and provide new insights into machine learning-based molecule representation and generation.
no code implementations • 5 Apr 2023 • Shuanghong Shen, Enhong Chen, Bihan Xu, Qi Liu, Zhenya Huang, Linbo Zhu, Yu Su
In this paper, we present the Quiz-based Knowledge Tracing (QKT) model to monitor students' knowledge states according to their quiz-based learning interactions.
no code implementations • 17 Mar 2023 • Jie Wang, Zhihao Shi, Xize Liang, Defu Lian, Shuiwang Ji, Bin Li, Enhong Chen, Feng Wu
During the message passing (MP) in GNNs, subgraph-wise sampling methods discard messages outside the mini-batches in backward passes to avoid the well-known neighbor explosion problem, i. e., the exponentially increasing dependencies of nodes with the number of MP iterations.
1 code implementation • 16 Mar 2023 • Shukang Yin, Shiwei Wu, Tong Xu, Shifeng Liu, Sirui Zhao, Enhong Chen
Automatic Micro-Expression (ME) spotting in long videos is a crucial step in ME analysis but also a challenging task due to the short duration and low intensity of MEs.
5 code implementations • 1 Mar 2023 • Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Enhong Chen
In this work, we propose TimeMAE, a novel self-supervised paradigm for learning transferrable time series representations based on transformer networks.
no code implementations • 1 Mar 2023 • Yongqiang Han, Likang Wu, Hao Wang, Guifeng Wang, Mengdi Zhang, Zhi Li, Defu Lian, Enhong Chen
Sequential Recommendation is a widely studied paradigm for learning users' dynamic interests from historical interactions for predicting the next potential item.
no code implementations • 23 Feb 2023 • Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen
To protect user privacy and meet legal regulations, federated learning (FL) is attracting significant attention.
3 code implementations • 20 Feb 2023 • Mingyue Cheng, Qi Liu, Zhiding Liu, Zhi Li, Yucong Luo, Enhong Chen
Deep learning-based algorithms, e. g., convolutional networks, have significantly facilitated multivariate time series classification (MTSC) task.
no code implementations • 9 Feb 2023 • Yuting Ning, Jiayu Liu, Longhu Qin, Tong Xiao, Shangzi Xue, Zhenya Huang, Qi Liu, Enhong Chen, Jinze Wu
In the Natural Language for Optimization (NL4Opt) NeurIPS 2022 competition, competitors focus on improving the accessibility and usability of optimization solvers, with the aim of subtask 1: recognizing the semantic entities that correspond to the components of the optimization problem; subtask 2: generating formulations for the optimization problem.
1 code implementation • 18 Jan 2023 • Yuting Ning, Zhenya Huang, Xin Lin, Enhong Chen, Shiwei Tong, Zheng Gong, Shijin Wang
To this end, in this paper, we propose a novel contrastive pre-training approach for mathematical question representations, namely QuesCo, which attempts to bring questions with more similar purposes closer.
no code implementations • 3 Jan 2023 • Sirui Zhao, Huaying Tang, Xinglong Mao, Shifeng Liu, Yiming Zhang, Hao Wang, Tong Xu, Enhong Chen
One of the most important subconscious reactions, micro-expression (ME), is a spontaneous, subtle, and transient facial expression that reveals human beings' genuine emotion.
no code implementations • 15 Nov 2022 • Zhihao Zhu, Chenwang Wu, Min Zhou, Hao Liao, Defu Lian, Enhong Chen
Recent studies show that Graph Neural Networks(GNNs) are vulnerable and easily fooled by small perturbations, which has raised considerable concerns for adapting GNNs in various safety-critical applications.
no code implementations • 9 Nov 2022 • Junzhe Jiang, Mingyue Cheng, Qi Liu, Zhi Li, Enhong Chen
Recognizing useful named entities plays a vital role in medical information processing, which helps drive the development of medical area research.
Medical Named Entity Recognition
named-entity-recognition
+3
1 code implementation • 5 Nov 2022 • Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen
The core idea of CANet is to route the input user behaviors with a light-weighted router module.