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ORCIDHaoran Tang
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2020 – today
- 2024
[c22]Meng Cao, Haoran Tang, Jinfa Huang, Peng Jin, Can Zhang, Ruyang Liu, Long Chen, Xiaodan Liang, Li Yuan, Ge Li:
RAP: Efficient Text-Video Retrieval with Sparse-and-Correlated Adapter. ACL (Findings) 2024: 7160-7174- [c21]Jingying Wang
, Haoran Tang, Taylor Kantor, Tandis Soltani, Vitaliy Popov, Xu Wang:
Surgment: Segmentation-enabled Semantic Search and Creation of Visual Question and Feedback to Support Video-Based Surgery Learning. CHI 2024: 461:1-461:18 - [c20]Ruyang Liu, Chen Li, Haoran Tang, Yixiao Ge, Ying Shan, Ge Li:
ST-LLM: Large Language Models Are Effective Temporal Learners. ECCV (57) 2024: 1-18 - [c19]Yicong Li, Yu Yang, Jiannong Cao, Shuaiqi Liu, Haoran Tang, Guandong Xu:
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach. KDD 2024: 1701-1712 - [c18]Kang Yi, Haoran Tang, Hongyu Bai, Yinjie Wang, Jing Xu, Ping Li:
Bi-directional Interaction and Dense Aggregation Network for RGB-D Salient Object Detection. MMM (1) 2024: 475-489 - [i18]Jingying Wang, Haoran Tang, Taylor Kantor, Tandis Soltani, Vitaliy Popov, Xu Wang:
Surgment: Segmentation-enabled Semantic Search and Creation of Visual Question and Feedback to Support Video-Based Surgery Learning. CoRR abs/2402.17903 (2024) - [i17]Ruyang Liu, Chen Li, Haoran Tang, Yixiao Ge, Ying Shan, Ge Li:
ST-LLM: Large Language Models Are Effective Temporal Learners. CoRR abs/2404.00308 (2024) - [i16]Xueyao Sun, Kaize Shi, Haoran Tang, Guandong Xu, Qing Li:
Expert-Guided Extinction of Toxic Tokens for Debiased Generation. CoRR abs/2405.19299 (2024) - [i15]Meng Cao, Haoran Tang, Jinfa Huang, Peng Jin, Can Zhang, Ruyang Liu, Long Chen, Xiaodan Liang, Li Yuan, Ge Li:
RAP: Efficient Text-Video Retrieval with Sparse-and-Correlated Adapter. CoRR abs/2405.19465 (2024) - [i14]Yicong Li, Yu Yang, Jiannong Cao, Shuaiqi Liu, Haoran Tang, Guandong Xu:
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach. CoRR abs/2406.13201 (2024) - [i13]Xiang Li, Haoran Tang, Siyu Chen, Ziwei Wang, Ryan Chen, Marcin Abram:
Why does in-context learning fail sometimes? Evaluating in-context learning on open and closed questions. CoRR abs/2407.02028 (2024) - [i12]Haoran Tang, Meng Cao, Jinfa Huang, Ruyang Liu, Peng Jin, Ge Li, Xiaodan Liang:
MUSE: Mamba is Efficient Multi-scale Learner for Text-video Retrieval. CoRR abs/2408.10575 (2024) - 2023
- [j5]Jun Zeng, Haoran Tang, Yizhu Zhao, Junhao Wen:
Neu-PCM: Neural-based potential correlation mining for POI recommendation. Appl. Intell. 53(9): 10685-10698 (2023) - [j4]Fengcheng Guo, Haoran Tang, Wensong Liu:
Non-Local Means De-Speckling Based on Multi-Directional Local Plane Inclination Angle. Remote. Sens. 15(4): 1029 (2023) - [c17]Kaihong Yan, Haoran Tang, Jian Zhang, Peng Peng, Hongwei Wang:
A Novel Encoder-Decoder Architecture for Table Border Segmentation of Scanned Documents. CSCWD 2023: 953-958 - [c16]Yuanyi Zhong, Haoran Tang, Jun-Kun Chen, Yu-Xiong Wang:
Contrastive Learning Relies More on Spatial Inductive Bias Than Supervised Learning: An Empirical Study. ICCV 2023: 16281-16290 - [c15]Haoran Tang, Shiqing Wu, Guandong Xu, Qing Li:
Dynamic Graph Evolution Learning for Recommendation. SIGIR 2023: 1589-1598 - [i11]Zixuan Wang, Haoran Tang, Haibo Wang, Bo Qin, Mark D. Butala, Weiming Shen, Hongwei Wang:
Weighted Joint Maximum Mean Discrepancy Enabled Multi-Source-Multi-Target Unsupervised Domain Adaptation Fault Diagnosis. CoRR abs/2310.14790 (2023) - [i10]Haoran Tang, Xin Zhou, Jieren Deng, Zhihong Pan, Hao Tian, Pratik Chaudhari:
Retrieving Conditions from Reference Images for Diffusion Models. CoRR abs/2312.02521 (2023) - [i9]Xiang Li, Haoran Tang, Siyu Chen, Ziwei Wang, Anurag Maravi, Marcin Abram:
Context Matters: Data-Efficient Augmentation of Large Language Models for Scientific Applications. CoRR abs/2312.07069 (2023) - 2022
- [j3]Hai Guo, Yifan Song, Haoran Tang, Jing-ying Zhao:
An ensemble deep neural network approach for predicting TOC concentration in lakes along the middle-lower reaches of Yangtze River. J. Intell. Fuzzy Syst. 42(3): 1455-1482 (2022) - [c14]Haoran Tang, Zhuoyang Wang, Jianhui Yang, Sichen Zhou:
Experimental research on the colour interpolation algorithm of the full colour image. CIPAE 2022: 6-11 - [c13]Kaihong Yan, Ying Zhang, Haoran Tang, Chengkai Ren, Jian Zhang, Gaoang Wang, Hongwei Wang:
Signature Detection, Restoration, and Verification: A Novel Chinese Document Signature Forgery Detection Benchmark. CVPR Workshops 2022: 5159-5168 - [c12]Haoran Tang, Jian Zhang, Kaihong Yan, Gaoang Wang, Hongwei Wang:
A Framework for Handwritten Date Recognition in Quality Documents. ICEBE 2022: 234-239 - [i8]Changwei Xu, Jianfei Yang, Haoran Tang, Han Zou, Cheng Lu, Tianshuo Zhang:
Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation. CoRR abs/2201.11963 (2022) - [i7]Yuanyi Zhong, Haoran Tang, Junkun Chen, Jian Peng, Yu-Xiong Wang:
Is Self-Supervised Learning More Robust Than Supervised Learning? CoRR abs/2206.05259 (2022) - [i6]Lukas Zhornyak, Zhengjie Xu, Haoran Tang, Jianbo Shi:
HashEncoding: Autoencoding with Multiscale Coordinate Hashing. CoRR abs/2211.15894 (2022) - [i5]Zeqian Li, Keyu Qiu, Chenxu Jiao, Wen Zhu, Haoran Tang:
WEKA-Based: Key Features and Classifier for French of Five Countries. CoRR abs/2212.08132 (2022) - 2021
- [j2]Jun Zeng, Xin He, Haoran Tang, Junhao Wen:
Predicting the next location: A self-attention and recurrent neural network model with temporal context. Trans. Emerg. Telecommun. Technol. 32(6) (2021) - [j1]Jun Zeng, Haoran Tang, Yizhu Zhao, Min Gao, Junhao Wen:
PR-RCUC: A POI Recommendation Model Using Region-Based Collaborative Filtering and User-Based Mobile Context. Mob. Networks Appl. 26(6): 2434-2444 (2021) - [c11]Haoran Tang, Changwei Xu, Jianfei Yang:
Bi-Adversarial Discrepancy Minimization for Unsupervised Domain Adaptation on 3D Point Cloud. IJCNN 2021: 1-8 - 2020
- [c10]Jun Zeng, Haoran Tang, Xin He:
RCFC: A Region-Based POI Recommendation Model with Collaborative Filtering and User Context. CollaborateCom (1) 2020: 656-670 - [c9]Jing-ying Zhao, Min Han, Hai Guo, Haoran Tang, Na Dong, Enming Zhao:
Bagging of Gaussian Process for Large Generator Eddy Current Prediction. ICACI 2020: 184-188 - [c8]Jun Zeng, Haoran Tang, Junhao Wen:
DPR-Geo: A POI Recommendation Model Using Deep Neural Network and Geographical Influence. ICONIP (3) 2020: 420-431
2010 – 2019
- 2019
- [c7]Jun Zeng, Xin He, Haoran Tang, Junhao Wen:
A Next Location Predicting Approach Based on a Recurrent Neural Network and Self-attention. CollaborateCom 2019: 309-322 - [c6]Jun Zeng, Haoran Tang, Yingbo Wu, Ling Liu, Sachio Hirokawa:
Predict the Next Location From Trajectory Based on Spatiotemporal Sequence. IIAI-AAI 2019: 109-114 - [c5]Jun Zeng, Haoran Tang, Yinghua Li, Xin He:
A Deep Learning Model Based on Sparse Matrix for Point-of-Interest Recommendation. SEKE 2019: 379-492 - [i4]Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine:
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR abs/1909.10618 (2019) - 2018
- [c4]Dennis Lee, Haoran Tang, Jeffrey O. Zhang, Huazhe Xu, Trevor Darrell, Pieter Abbeel:
Modular Architecture for StarCraft II with Deep Reinforcement Learning. AIIDE 2018: 187-193 - [i3]Dennis Lee, Haoran Tang, Jeffrey O. Zhang, Huazhe Xu, Trevor Darrell, Pieter Abbeel:
Modular Architecture for StarCraft II with Deep Reinforcement Learning. CoRR abs/1811.03555 (2018) - 2017
- [c3]Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine:
Reinforcement Learning with Deep Energy-Based Policies. ICML 2017: 1352-1361 - [c2]Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel:
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. NIPS 2017: 2753-2762 - [i2]Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine:
Reinforcement Learning with Deep Energy-Based Policies. CoRR abs/1702.08165 (2017) - 2016
- [c1]Daniela Ushizima, Chao Yang, Singanallur V. Venkatakrishnan, Flávio H. D. Araújo, Romuere Rôdrigues Veloso e Silva, Haoran Tang, Joao Vitor Mascarenhas, Alexander Hexemer, Dilworth Parkinson, James A. Sethian:
Convolutional neural networks at the interface of physical and digital data. AIPR 2016: 1-12 - [i1]Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel:
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. CoRR abs/1611.04717 (2016)
Coauthor Index
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