Zheda Mai

According to our database, Zheda Mai authored at least 31 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

AVA-Bench: Atomic Visual Ability Benchmark for Vision Foundation Models.

Zheda Mai, Arpita Chowdhury, Zihe Wang, Sooyoung Jeon, Lemeng Wang, Jiacheng Hou, Jihyung Kil, Wei-Lun Chao

CoRR, June, 2025

BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning.

Jianyang Gu, Samuel Stevens, Elizabeth G. Campolongo, Matthew J. Thompson, Net Zhang, Jiaman Wu, Andrei Kopanev, Zheda Mai, Alexander E. White, James P. Balhoff, Wasila M. Dahdul, Daniel I. Rubenstein, Hilmar Lapp, Tanya Y. Berger-Wolf, Wei-Lun Chao, Yu Su

CoRR, May, 2025

Revisiting semi-supervised learning in the era of foundation models.

Ping Zhang, Zheda Mai, Quang-Huy Nguyen, Wei-Lun Chao

CoRR, March, 2025

Prompt-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis.

Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G. Campolongo, Daniel I. Rubenstein, Charles V. Stewart, Anuj Karpatne, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao

CoRR, January, 2025

MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference.

Zhongwei Wan, Hui Shen, Xin Wang, Che Liu, Zheda Mai, Mi Zhang

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Attention-Driven Causal Discovery: From Transformer Matrices to Granger Causal Graphs for Non-Stationary Time-series Data.

Jiageng Zhu, Kehao Li, Zheda Mai, Hanchen Xie, Wael AbdAlmageed, Zubin Abraham

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation.

Ziheng Zhang, Jianyang Gu, Arpita Chowdhury, Zheda Mai, David Carlyn, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Efficiently Mitigating Video Content Misalignment on Large Vision Model with Time-Series Data Alignment.

Hanchen Xie, Rose Ma, Jiageng Zhu, Zheda Mai, Wael Abd-Almageed, Zubin Abraham

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition.

Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Quang-Huy Nguyen, Li Zhang, Wei-Lun Chao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis.

Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G. Campolongo, Daniel I. Rubenstein, Charles V. Stewart, Anuj Karpatne, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition.

Zheda Mai, Ping Zhang, Cheng-Hao Tu, Hong-You Chen, Li Zhang, Wei-Lun Chao

CoRR, 2024

CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs.

Jihyung Kil, Zheda Mai, Justin Lee, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Arpita Chowdhury, Wei-Lun Chao

CoRR, 2024

Fine-Tuning is Fine, if Calibrated.

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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

MLLM-CompBench: A Comparative Reasoning Benchmark for Multimodal LLMs.

Jihyung Kil, Zheda Mai, Justin Lee, Arpita Chowdhury, Zihe Wang, Kerrie Cheng, Lemeng Wang, Ye Liu, Wei-Lun Chao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation.

Ruiwen Li, Zheda Mai, Zhibo Zhang, Jongseong Jang, Scott Sanner

J. Vis. Commun. Image Represent., April, 2023

Towards understanding and mitigating unintended biases in language model-driven conversational recommendation.

Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner

Inf. Process. Manag., 2023

Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation.

Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao

CoRR, 2023

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning.

Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Online continual learning in image classification: An empirical survey.

Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner

Neurocomputing, 2022

TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation.

Ruiwen Li, Zheda Mai, Chiheb Trabelsi, Zhibo Zhang, Jongseong Jang, Scott Sanner

CoRR, 2022

Unintended Bias in Language Model-driven Conversational Recommendation.

Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner

CoRR, 2022

CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions.

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

Artif. Intell., 2022

Distributional Contrastive Embedding for Clarification-based Conversational Critiquing.

Tianshu Shen, Zheda Mai, Ga Wu, Scott Sanner

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems.

Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021

Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning.

Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Online Class-Incremental Continual Learning with Adversarial Shapley Value.

Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adversarial Shapley Value Experience Replay for Task-Free Continual Learning.

Zheda Mai, Dongsub Shim, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang

CoRR, 2020

Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering.

Jin Peng Zhou, Ga Wu, Zheda Mai, Scott Sanner

CoRR, 2020

Batch-level Experience Replay with Review for Continual Learning.

Zheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott Sanner

CoRR, 2020

Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering.

Zheda Mai, Ga Wu, Kai Luo, Scott Sanner

Proceedings of the 20th International Conference on Data Mining Workshops, 2020