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ORCIDACM Transactions on Information Systems, Volume 42
Volume 42, Number 1, January 2024
- Lanning Wei
, Huan Zhao, Zhiqiang He, Quanming Yao:
Neural Architecture Search for GNN-Based Graph Classification. 1:1-1:29 - Molly McGregor, Leif Azzopardi, Martin Halvey:
A Systematic Review of Cost, Effort, and Load Research in Information Search and Retrieval, 1972-2020. 2:1-2:39 - Hongyan Xu, Qiyao Peng, Hongtao Liu, Yueheng Sun, Wenjun Wang:
Group-Based Personalized News Recommendation with Long- and Short-Term Fine-Grained Matching. 3:1-3:27 - Jin Zhang, Xinrui Li, Liye Wang:
A Review Selection Method Based on Consumer Decision Phases in E-commerce. 4:1-4:27 - Yao Wu, Jian Cao, Guandong Xu:
FASTER: A Dynamic Fairness-assurance Strategy for Session-based Recommender Systems. 5:1-5:26 - Xinhang Li, Zhaopeng Qiu, Jiacheng Jiang, Yong Zhang, Chunxiao Xing, Xian Wu:
Conditional Cross-Platform User Engagement Prediction. 6:1-6:28 - Radin Hamidi Rad, Hossein Fani, Ebrahim Bagheri, Mehdi Kargar, Divesh Srivastava, Jaroslaw Szlichta:
A Variational Neural Architecture for Skill-based Team Formation. 7:1-7:28 - Liangliang He, Xiao Li, Pancheng Wang, Jintao Tang, Ting Wang:
MAN: Memory-augmented Attentive Networks for Deep Learning-based Knowledge Tracing. 8:1-8:22 - Hai Chen, Fulan Qian, Chang Liu, Yanping Zhang, Hang Su, Shu Zhao:
Training Robust Deep Collaborative Filtering Models via Adversarial Noise Propagation. 9:1-9:27 - Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun, Fan Liu, Fuming Sun, Haojie Li:
Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation. 10:1-10:26 - Tetsuya Sakai, Jinyoung Kim, Inho Kang:
A Versatile Framework for Evaluating Ranked Lists in Terms of Group Fairness and Relevance. 11:1-11:36 - Wenjie Wang, Xinyu Lin, Liuhui Wang, Fuli Feng, Yunshan Ma, Tat-Seng Chua:
Causal Disentangled Recommendation against User Preference Shifts. 12:1-12:27 - Yazhou Zhang, Ao Jia, Bo Wang, Peng Zhang, Dongming Zhao, Pu Li, Yuexian Hou, Xiaojia Jin, Dawei Song, Jing Qin:
M3GAT: A Multi-modal, Multi-task Interactive Graph Attention Network for Conversational Sentiment Analysis and Emotion Recognition. 13:1-13:32 - Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang:
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System. 14:1-14:27 - Zhu Sun, Yu Lei, Lu Zhang, Chen Li, Yew-Soon Ong, Jie Zhang:
A Multi-channel Next POI Recommendation Framework with Multi-granularity Check-in Signals. 15:1-15:28 - Dongjing Wang, Xin Zhang, Yuyu Yin, Dongjin Yu, Guandong Xu, Shuiguang Deng:
Multi-View Enhanced Graph Attention Network for Session-Based Music Recommendation. 16:1-16:30 - Weiwei Sun, Shuyu Guo, Shuo Zhang, Pengjie Ren, Zhumin Chen, Maarten de Rijke, Zhaochun Ren:
Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systems. 17:1-17:29 - Yingrong Qin, Chen Gao, Shuangqing Wei, Yue Wang, Depeng Jin, Jian Yuan, Lin Zhang, Dong Li, Jianye Hao, Yong Li:
Learning from Hierarchical Structure of Knowledge Graph for Recommendation. 18:1-18:24 - Lida Rashidi, Justin Zobel, Alistair Moffat:
The Impact of Judgment Variability on the Consistency of Offline Effectiveness Measures. 19:1-19:31 - Sebastian Bruch, Siyu Gai, Amir Ingber:
An Analysis of Fusion Functions for Hybrid Retrieval. 20:1-20:35 - Kevin Roitero, David La Barbera, Michael Soprano, Gianluca Demartini, Stefano Mizzaro, Tetsuya Sakai:
How Many Crowd Workers Do I Need? On Statistical Power when Crowdsourcing Relevance Judgments. 21:1-21:26 - Heyan Huang, Changsen Yuan, Qian Liu, Yixin Cao:
Document-level Relation Extraction via Separate Relation Representation and Logical Reasoning. 22:1-22:24 - Tetsuya Sakai, Sijie Tao, Nuo Chen, Yujing Li, Maria Maistro, Zhumin Chu, Nicola Ferro:
On the Ordering of Pooled Web Pages, Gold Assessments, and Bronze Assessments. 23:1-23:31 - Qing Yin, Hui Fang, Zhu Sun, Yew-Soon Ong:
Understanding Diversity in Session-based Recommendation. 24:1-24:34 - Liqiang Jing, Xuemeng Song, Xuming Lin, Zhongzhou Zhao, Wei Zhou, Liqiang Nie:
Stylized Data-to-text Generation: A Case Study in the E-Commerce Domain. 25:1-25:24 - Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu:
Invariant Node Representation Learning under Distribution Shifts with Multiple Latent Environments. 26:1-26:30 - Chuan Qin, Hengshu Zhu, Dazhong Shen, Ying Sun, Kaichun Yao, Peng Wang, Hui Xiong:
Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job Interviews. 27:1-27:32 - Yuxin Ni, Yunwen Xia, Hui Fang, Chong Long, Xinyu Kong, Daqian Li, Dong Yang, Jie Zhang:
Meta-CRS: A Dynamic Meta-Learning Approach for Effective Conversational Recommender System. 28:1-28:27 - Zhichao Xu, Hansi Zeng, Juntao Tan, Zuohui Fu, Yongfeng Zhang, Qingyao Ai:
A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability. 29:1-29:29 - Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. 30:1-30:27 - Josiane Mothe, Md. Zia Ullah:
Selective Query Processing: A Risk-Sensitive Selection of Search Configurations. 31:1-31:35 - Zifeng Cheng, Qingyu Zhou, Zhiwei Jiang, Xuemin Zhao, Yunbo Cao, Qing Gu:
Unifying Token- and Span-level Supervisions for Few-shot Sequence Labeling. 32:1-32:27
Volume 42, Number 2, March 2024
- Yang Yang, Chubing Zhang, Xin Song, Zheng Dong, Hengshu Zhu, Wenjie Li:
Contextualized Knowledge Graph Embedding for Explainable Talent Training Course Recommendation. 33:1-33:27 - Yitong Yao, Jing Zhang, Peng Zhang, Yueheng Sun:
A Dual-branch Learning Model with Gradient-balanced Loss for Long-tailed Multi-label Text Classification. 34:1-34:24 - Tian Lan, Xian-Ling Mao, Wei Wei, Xiaoyan Gao, Heyan Huang:
Towards Efficient Coarse-grained Dialogue Response Selection. 35:1-35:32 - Canjia Li, Andrew Yates, Sean MacAvaney, Ben He, Yingfei Sun:
PARADE: Passage Representation Aggregation forDocument Reranking. 36:1-36:26 - Jiayi Xie, Zhenzhong Chen:
Hierarchical Transformer with Spatio-temporal Context Aggregation for Next Point-of-interest Recommendation. 37:1-37:30 - Chen Xu, Jun Xu, Zhenhua Dong, Ji-Rong Wen:
Syntactic-Informed Graph Networks for Sentence Matching. 38:1-38:29 - Xinyu Zhang, Kelechi Ogueji, Xueguang Ma, Jimmy Lin:
Toward Best Practices for Training Multilingual Dense Retrieval Models. 39:1-39:33 - Yixiao Ma, Yueyue Wu, Qingyao Ai, Yiqun Liu, Yunqiu Shao, Min Zhang, Shaoping Ma:
Incorporating Structural Information into Legal Case Retrieval. 40:1-40:28 - Yatong Sun, Xiaochun Yang, Zhu Sun, Bin Wang:
BERD+: A Generic Sequential Recommendation Framework by Eliminating Unreliable Data with Item- and Attribute-level Signals. 41:1-41:33 - Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty:
An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors. 42:1-42:43 - Shengyu Zhang, Tan Jiang, Kun Kuang, Fuli Feng, Jin Yu, Jianxin Ma, Zhou Zhao, Jianke Zhu, Hongxia Yang, Tat-Seng Chua, Fei Wu:
SLED: Structure Learning based Denoising for Recommendation. 43:1-43:31 - Yuhan Quan, Jingtao Ding, Chen Gao, Nian Li, Lingling Yi, Depeng Jin, Yong Li:
Alleviating Video-length Effect for Micro-video Recommendation. 44:1-44:24 - Sannyuya Liu, Shengyingjie Liu, Zongkai Yang, Jianwen Sun, Xiaoxuan Shen, Qing Li, Rui Zou, Shangheng Du:
Heterogeneous Evolution Network Embedding with Temporal Extension for Intelligent Tutoring Systems. 45:1-45:28 - Yanrui Niu, Chao Liang, Ankang Lu, Baojin Huang, Zhongyuan Wang, Jiahao Guo:
Person-action Instance Search in Story Videos: An Experimental Study. 46:1-46:34 - Han Liu, Yinwei Wei, Fan Liu, Wenjie Wang, Liqiang Nie, Tat-Seng Chua:
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation. 47:1-47:26 - Lei Guo, Hao Liu, Lei Zhu, Weili Guan, Zhiyong Cheng:
DA-DAN: A Dual Adversarial Domain Adaption Network for Unsupervised Non-overlapping Cross-domain Recommendation. 48:1-48:27 - Longxuan Ma, Jiapeng Li, Mingda Li, Weinan Zhang, Ting Liu:
Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialogue. 49:1-49:29 - Yupeng Hu, Kun Wang, Meng Liu, Haoyu Tang, Liqiang Nie:
Semantic Collaborative Learning for Cross-Modal Moment Localization. 50:1-50:26 - Ke Wang, Yanmin Zhu, Tianzi Zang, Chunyang Wang, Kuan Liu, Peibo Ma:
Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation. 51:1-51:29 - Xiaoyu Shi, Quanliang Liu, Hong Xie, Di Wu, Bo Peng, Mingsheng Shang, Defu Lian:
Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach. 52:1-52:30 - Xiaolin Chen, Xuemeng Song, Liqiang Jing, Shuo Li, Linmei Hu, Liqiang Nie:
Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language Model. 53:1-53:25 - Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion Model for POI Recommendation. 54:1-54:27 - Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke:
Understanding and Predicting User Satisfaction with Conversational Recommender Systems. 55:1-55:37 - Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Enhong Chen, Hui Xiong:
SetRank: A Setwise Bayesian Approach for Collaborative Ranking in Recommender System. 56:1-56:32 - Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng:
NIR-Prompt: A Multi-task Generalized Neural Information Retrieval Training Framework. 57:1-57:32 - Zhongwei Wan, Xin Liu, Benyou Wang, Jiezhong Qiu, Boyu Li, Ting Guo, Guangyong Chen, Yang Wang:
Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation. 58:1-58:26 - Mengyuan Jing, Yanmin Zhu, Tianzi Zang, Ke Wang:
Contrastive Self-supervised Learning in Recommender Systems: A Survey. 59:1-59:39 - Zixuan Yi, Iadh Ounis, Craig MacDonald:
Contrastive Graph Prompt-tuning for Cross-domain Recommendation. 60:1-60:28 - Elias Bassani, Nicola Tonellotto, Gabriella Pasi:
Personalized Query Expansion with Contextual Word Embeddings. 61:1-61:35 - Yunqiu Shao, Haitao Li, Yueyue Wu, Yiqun Liu, Qingyao Ai, Jiaxin Mao, Yixiao Ma, Shaoping Ma:
An Intent Taxonomy of Legal Case Retrieval. 62:1-62:27
Volume 42, Number 3, May 2024
- Zhizhuo Yin, Kai Han, Pengzi Wang, Xi Zhu:
H3GNN: Hybrid Hierarchical HyperGraph Neural Network for Personalized Session-based Recommendation. 63:1-63:30 - Wei Yuan, Shilong Yuan, Chaoqun Yang, Nguyen Quoc Viet Hung, Hongzhi Yin:
Manipulating Visually Aware Federated Recommender Systems and Its Countermeasures. 64:1-64:26 - Bogeum Choi, Sarah Casteel, Jaime Arguello, Robert Capra:
Better Understanding Procedural Search Tasks: Perceptions, Behaviors, and Challenges. 65:1-65:32 - Zihao Li, Aixin Sun, Chenliang Li:
DiffuRec: A Diffusion Model for Sequential Recommendation. 66:1-66:28 - Xuelian Ni, Fei Xiong, Shirui Pan, Jia Wu, Liang Wang, Hongshu Chen:
Community Preserving Social Recommendation with Cyclic Transfer Learning. 67:1-67:36 - Xiaokun Zhang, Bo Xu, Fenglong Ma, Chenliang Li, Yuan Lin, Hongfei Lin:
Bi-preference Learning Heterogeneous Hypergraph Networks for Session-based Recommendation. 68:1-68:28 - Fernando Giner:
Information Retrieval Evaluation Measures Defined on Some Axiomatic Models of Preferences. 69:1-69:35 - Yuting Zhang, Ying Sun, Fuzhen Zhuang, Yongchun Zhu, Zhulin An, Yongjun Xu:
Triple Dual Learning for Opinion-based Explainable Recommendation. 70:1-70:27 - Yitao Zhang, Changxuan Wan, Keli Xiao, Qizhi Wan, Dexi Liu, Xiping Liu:
rHDP: An Aspect Sharing-Enhanced Hierarchical Topic Model for Multi-Domain Corpus. 71:1-71:31 - Kaixi Hu, Lin Li, Qing Xie, Jianquan Liu, Xiaohui Tao, Guandong Xu:
Decoupled Progressive Distillation for Sequential Prediction with Interaction Dynamics. 72:1-72:35 - Mark Stevenson, Reem Bin Hezam:
Stopping Methods for Technology-assisted Reviews Based on Point Processes. 73:1-73:37 - Lang Mei, Jiaxin Mao, Juan Hu, Naiqiang Tan, Hua Chai, Ji-Rong Wen:
Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models. 74:1-74:27 - Jiaxin Wu, Chong-Wah Ngo, Wing-Kwong Chan, Zhijian Hou:
(Un)likelihood Training for Interpretable Embedding. 75:1-75:26 - Tianzi Zang, Yanmin Zhu, Ruohan Zhang, Chunyang Wang, Ke Wang, Jiadi Yu:
Contrastive Multi-view Interest Learning for Cross-domain Sequential Recommendation. 76:1-76:30 - Antonios Minas Krasakis, Andrew Yates, Evangelos Kanoulas:
Contextualizing and Expanding Conversational Queries without Supervision. 77:1-77:30 - Chaoran Cui, Yumo Yao, Chunyun Zhang, Hebo Ma, Yuling Ma, Zhaochun Ren, Chen Zhang, James Ko:
DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracing. 78:1-78:24 - Dominika Michalkova, Mario Parra-Rodriguez, Yashar Moshfeghi:
Understanding Feeling-of-Knowing in Information Search: An EEG Study. 79:1-79:30 - An Zhang, Wenchang Ma, Jingnan Zheng, Xiang Wang, Tat-Seng Chua:
Robust Collaborative Filtering to Popularity Distribution Shift. 80:1-80:25 - Shuting Wang, Zhicheng Dou, Jiongnan Liu, Qiannan Zhu, Ji-Rong Wen:
Personalized and Diversified: Ranking Search Results in an Integrated Way. 81:1-81:25 - Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang:
Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning. 82:1-82:29 - Hongzu Su, Jingjing Li, Zhekai Du, Lei Zhu, Ke Lu, Heng Tao Shen:
Cross-domain Recommendation via Dual Adversarial Adaptation. 83:1-83:26 - Tian Lan, Deng Cai, Yan Wang, Yixuan Su, Heyan Huang, Xian-Ling Mao:
Exploring Dense Retrieval for Dialogue Response Selection. 84:1-84:29 - Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine:
Less is More: Removing Redundancy of Graph Convolutional Networks for Recommendation. 85:1-85:26 - Jingtong Gao, Xiangyu Zhao, Muyang Li, Minghao Zhao, Runze Wu, Ruocheng Guo, Yiding Liu, Dawei Yin:
SMLP4Rec: An Efficient All-MLP Architecture for Sequential Recommendations. 86:1-86:23 - Jiechen Xu, Lei Han, Shazia Wasim Sadiq, Gianluca Demartini:
On the Impact of Showing Evidence from Peers in Crowdsourced Truthfulness Assessments. 87:1-87:26
Volume 42, Number 4, July 2024
- Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li:
Causal Inference in Recommender Systems: A Survey and Future Directions. 88:1-88:32 - Wayne Xin Zhao, Jing Liu, Ruiyang Ren, Ji-Rong Wen:
Dense Text Retrieval Based on Pretrained Language Models: A Survey. 89:1-89:60 - Zhengbang Zhu, Rongjun Qin, Junjie Huang, Xinyi Dai, Yang Yu, Yong Yu, Weinan Zhang:
Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems. 90:1-90:32 - Haokai Ma, Ruobing Xie, Lei Meng, Xin Chen, Xu Zhang, Leyu Lin, Jie Zhou:
Triple Sequence Learning for Cross-domain Recommendation. 91:1-91:29 - Hédi Razgallah, Michalis Vlachos, Ahmad Ajalloeian, Ninghao Liu, Johannes Schneider, Alexis Steinmann:
Using Neural and Graph Neural Recommender Systems to Overcome Choice Overload: Evidence From a Music Education Platform. 92:1-92:26 - Ziyi Ye, Xiaohui Xie, Qingyao Ai, Yiqun Liu, Zhihong Wang, Weihang Su, Min Zhang:
Relevance Feedback with Brain Signals. 93:1-93:37 - Wei Chen, Yiqing Wu, Zhao Zhang, Fuzhen Zhuang, Zhongshi He, Ruobing Xie, Feng Xia:
FairGap: Fairness-Aware Recommendation via Generating Counterfactual Graph. 94:1-94:25 - Tung Thanh Vuong, Tuukka Ruotsalo:
Predicting Representations of Information Needs from Digital Activity Context. 95:1-95:29 - Yutong Bai, Yujia Zhou, Zhicheng Dou, Ji-Rong Wen:
Intent-Oriented Dynamic Interest Modeling for Personalized Web Search. 96:1-96:30 - Hao Liu, Lei Guo, Lei Zhu, Yongqiang Jiang, Min Gao, Hongzhi Yin:
MCRPL: A Pretrain, Prompt, and Fine-tune Paradigm for Non-overlapping Many-to-one Cross-domain Recommendation. 97:1-97:24 - Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu:
On the Effectiveness of Sampled Softmax Loss for Item Recommendation. 98:1-98:26 - John P. Lalor, Ahmed Abbasi, Kezia Oketch, Yi Yang, Nicole Forsgren:
Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines. 99:1-99:41 - Yunshan Ma, Yingzhi He, Xiang Wang, Yinwei Wei, Xiaoyu Du, Yuyangzi Fu, Tat-Seng Chua:
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation. 100:1-100:23 - Jiezhu Cheng, Kaizhu Huang, Zibin Zheng:
Can Perturbations Help Reduce Investment Risks? Risk-aware Stock Recommendation via Split Variational Adversarial Training. 101:1-101:28 - Shangkun Che, Hongyan Liu, Shen Liu:
Tagging Items with Emerging Tags: A Neural Topic Model Based Few-Shot Learning Approach. 102:1-102:37 - Shengyu Zhang, Qiaowei Miao, Ping Nie, Mengze Li, Zhengyu Chen, Fuli Feng, Kun Kuang, Fei Wu:
Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation. 103:1-103:27 - Qizhi Wan, Changxuan Wan, Keli Xiao, Hui Xiong, Dexi Liu, Xiping Liu, Rong Hu:
Token-Event-Role Structure-Based Multi-Channel Document-Level Event Extraction. 104:1-104:27 - Shuzhe Li, Wei Chen, Bin Wang, Chao Huang, Yanwei Yu, Junyu Dong:
MCN4Rec: Multi-level Collaborative Neural Network for Next Location Recommendation. 105:1-105:26 - Xiangmeng Wang, Qian Li, Dianer Yu, Qing Li, Guandong Xu:
Counterfactual Explanation for Fairness in Recommendation. 106:1-106:30 - Yang Fang, Xiang Zhao, Weidong Xiao, Maarten de Rijke:
Few-shot Learning for Heterogeneous Information Networks. 107:1-107:24 - Jun Li, Yi Bin, Yunshan Ma, Yang Yang, Zi Huang, Tat-Seng Chua:
Filter-based Stance Network for Rumor Verification. 108:1-108:28 - Shujie Li, Guanghu Yuan, Min Yang, Ying Shen, Chengming Li, Ruifeng Xu, Xiaoyan Zhao:
Improving Semi-Supervised Text Classification with Dual Meta-Learning. 109:1-109:28 - Rui Zha, Ying Sun, Chuan Qin, Le Zhang, Tong Xu, Hengshu Zhu, Enhong Chen:
Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph. 110:1-110:28 - Tianshi Wang, Fengling Li, Lei Zhu, Jingjing Li, Zheng Zhang, Heng Tao Shen:
Invisible Black-Box Backdoor Attack against Deep Cross-Modal Hashing Retrieval. 111:1-111:27 - Yanjun Pu, Fang Liu, Rongye Shi, Haitao Yuan, Ruibo Chen, Tianhao Peng, Wenjun Wu:
ELAKT: Enhancing Locality for Attentive Knowledge Tracing. 112:1-112:27
Volume 42, Number 5, September 2024
- Sebastian Bruch, Claudio Lucchese, Maria Maistro, Franco Maria Nardini:
Special Section on Efficiency in Neural Information Retrieval. 113:1-113:4 - David Rau, Mostafa Dehghani, Jaap Kamps:
Revisiting Bag of Words Document Representations for Efficient Ranking with Transformers. 114:1-114:27 - Arian Askari, Suzan Verberne, Amin Abolghasemi, Wessel Kraaij, Gabriella Pasi:
Retrieval for Extremely Long Queries and Documents with RPRS: A Highly Efficient and Effective Transformer-based Re-Ranker. 115:1-115:32 - Thibault Formal, Carlos Lassance, Benjamin Piwowarski, Stéphane Clinchant:
Towards Effective and Efficient Sparse Neural Information Retrieval. 116:1-116:46 - Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand:
Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders. 117:1-117:34 - Qi Liu, Gang Guo, Jiaxin Mao, Zhicheng Dou, Ji-Rong Wen, Hao Jiang, Xinyu Zhang, Zhao Cao:
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models. 118:1-118:28 - Abhijit Anand, Jurek Leonhardt, Jaspreet Singh, Koustav Rudra, Avishek Anand:
Data Augmentation for Sample Efficient and Robust Document Ranking. 119:1-119:29 - Surong Yan, Chenglong Shi, Haosen Wang, Lei Chen, Ling Jiang, Ruilin Guo, Kwei-Jay Lin:
Teach and Explore: A Multiplex Information-guided Effective and Efficient Reinforcement Learning for Sequential Recommendation. 120:1-120:26
- Yen-Chieh Lien, Hamed Zamani, W. Bruce Croft:
Generalized Weak Supervision for Neural Information Retrieval. 121:1-121:26 - Alexander Frummet, Alessandro Speggiorin, David Elsweiler, Anton Leuski, Jeff Dalton:
Cooking with Conversation: Enhancing User Engagement and Learning with a Knowledge-Enhancing Assistant. 122:1-122:29 - Yunchang Zhu, Liang Pang, Kangxi Wu, Yanyan Lan, Huawei Shen, Xueqi Cheng:
Cross-Model Comparative Loss for Enhancing Neuronal Utility in Language Understanding. 123:1-123:29 - Jian Wang, Dongding Lin, Wenjie Li:
Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue. 124:1-124:27 - Enyue Yang, Weike Pan, Qiang Yang, Zhong Ming:
Discrete Federated Multi-behavior Recommendation for Privacy-Preserving Heterogeneous One-Class Collaborative Filtering. 125:1-125:50 - Zhirui Deng, Zhicheng Dou, Zhan Su, Ji-Rong Wen:
Multi-grained Document Modeling for Search Result Diversification. 126:1-126:22 - Kun Yi, Qi Zhang, Hui He, Kaize Shi, Liang Hu, Ning An, Zhendong Niu:
Deep Coupling Network for Multivariate Time Series Forecasting. 127:1-127:28 - Hanzhe Li, Jingjing Gu, Xinjiang Lu, Dazhong Shen, Yuting Liu, YaNan Deng, Guoliang Shi, Hui Xiong:
Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation. 128:1-128:31 - Xing Tang, Ling Chen, Hongyu Shi, Dandan Lyu:
DHyper: A Recurrent Dual Hypergraph Neural Network for Event Prediction in Temporal Knowledge Graphs. 129:1-129:23 - Junfan Chen, Richong Zhang, Xiaohan Jiang, Chunming Hu:
SPContrastNet: A Self-Paced Contrastive Learning Model for Few-Shot Text Classification. 130:1-130:25 - Hao Yang, Xian Wu, Zhaopeng Qiu, Yefeng Zheng, Xu Chen:
Distributional Fairness-aware Recommendation. 131:1-131:28 - Chaoyu Shi, Pengjie Ren, Dongjie Fu, Xin Xin, Shansong Yang, Fei Cai, Zhaochun Ren, Zhumin Chen:
Diversifying Sequential Recommendation with Retrospective and Prospective Transformers. 132:1-132:37 - Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng:
Listwise Generative Retrieval Models via a Sequential Learning Process. 133:1-133:31 - Zhiyuan Wen, Jiannong Cao, Jiaxing Shen, Ruosong Yang, Shuaiqi Liu, Maosong Sun:
Personality-affected Emotion Generation in Dialog Systems. 134:1-134:27 - Changxin Tian, Yuexiang Xie, Xu Chen, Yaliang Li, Xin Zhao:
Privacy-preserving Cross-domain Recommendation with Federated Graph Learning. 135:1-135:29 - Zhan Su, Zhicheng Dou, Yutao Zhu, Ji-Rong Wen:
Passage-aware Search Result Diversification. 136:1-136:29 - Xinghua Zhang, Bowen Yu, Xin Cong, Taoyu Su, Quangang Li, Tingwen Liu, Hongbo Xu:
Cross-Domain NER under a Divide-and-Transfer Paradigm. 137:1-137:32 - Yu-Xiang Zhang, Junjie Wang, Xinyu Zhu, Tetsuya Sakai, Hayato Yamana:
SSR: Solving Named Entity Recognition Problems via a Single-stream Reasoner. 138:1-138:28 - Fei Liu, Chenyang Bu, Haotian Zhang, Le Wu, Kui Yu, Xuegang Hu:
FDKT: Towards an Interpretable Deep Knowledge Tracing via Fuzzy Reasoning. 139:1-139:26 - Pengyang Shao, Le Wu, Kun Zhang, Defu Lian, Richang Hong, Yong Li, Meng Wang:
Average User-Side Counterfactual Fairness for Collaborative Filtering. 140:1-140:26
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