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ORCIDZheda Mai
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2020 – today
- 2024
[i15]Jihyung Kil, Zheda Mai, Justin Lee, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Arpita Chowdhury, Wei-Lun Chao:
CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs. CoRR abs/2407.16837 (2024)- [i14]Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Fine-Tuning is Fine, if Calibrated. CoRR abs/2409.16223 (2024) - [i13]Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Li Zhang, Wei-Lun Chao:
Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition. CoRR abs/2409.16434 (2024) - 2023
- [j4]Tianshu Shen
, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner:
Towards understanding and mitigating unintended biases in language model-driven conversational recommendation. Inf. Process. Manag. 60(1): 103139 (2023) - [j3]Ruiwen Li, Zheda Mai, Zhibo Zhang, Jongseong Jang, Scott Sanner:
TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation. J. Vis. Commun. Image Represent. 92: 103800 (2023) - [c7]Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao:
Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. CVPR 2023: 7725-7735 - [c6]Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. NeurIPS 2023 - [i12]Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao:
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation. CoRR abs/2305.05803 (2023) - [i11]Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Y. Berger-Wolf, Song Gao, Charles V. Stewart, Yu Su, Wei-Lun Chao:
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. CoRR abs/2311.01420 (2023) - 2022
- [j2]Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vázquez, German Ignacio Parisi, Nikhil Churamani, Marc Pickett, Issam H. Laradji, Davide Maltoni:
CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions. Artif. Intell. 303: 103635 (2022) - [j1]Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner:
Online continual learning in image classification: An empirical survey. Neurocomputing 469: 28-51 (2022) - [c5]Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner:
Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems. SIGIR 2022: 2524-2531 - [c4]Tianshu Shen, Zheda Mai, Ga Wu, Scott Sanner:
Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. WWW 2022: 2422-2432 - [i10]Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner:
Unintended Bias in Language Model-driven Conversational Recommendation. CoRR abs/2201.06224 (2022) - [i9]Ruiwen Li, Zheda Mai, Chiheb Trabelsi, Zhibo Zhang, Jongseong Jang, Scott Sanner:
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation. CoRR abs/2203.07239 (2022) - [i8]Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao:
Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. CoRR abs/2212.03220 (2022) - 2021
- [c3]Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang:
Online Class-Incremental Continual Learning with Adversarial Shapley Value. AAAI 2021: 9630-9638 - [c2]Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner:
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. CVPR Workshops 2021: 3589-3599 - [i7]Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner:
Online Continual Learning in Image Classification: An Empirical Survey. CoRR abs/2101.10423 (2021) - [i6]Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner:
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. CoRR abs/2103.13885 (2021) - 2020
- [c1]Zheda Mai, Ga Wu, Kai Luo, Scott Sanner:
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. ICDM (Workshops) 2020: 165-172 - [i5]Zheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott Sanner:
Batch-level Experience Replay with Review for Continual Learning. CoRR abs/2007.05683 (2020) - [i4]Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner:
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering. CoRR abs/2008.01246 (2020) - [i3]Zheda Mai, Dongsub Shim, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang:
Adversarial Shapley Value Experience Replay for Task-Free Continual Learning. CoRR abs/2009.00093 (2020) - [i2]Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vázquez, German Ignacio Parisi, Nikhil Churamani, Marc Pickett, Issam H. Laradji, Davide Maltoni:
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions. CoRR abs/2009.09929 (2020) - [i1]Zheda Mai, Ga Wu, Kai Luo, Scott Sanner:
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. CoRR abs/2010.12803 (2020)
Coauthor Index
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last updated on 2024-11-14 22:05 CET by the dblp team
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