Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. - Zheda Mai; Ga Wu; Kai Luo; Scott Sanner (ICDM (Workshops), 2020)

Batch-level Experience Replay with Review for Continual Learning. - Zheda Mai; Hyunwoo Kim; Jihwan Jeong; Scott Sanner (CoRR, 2020)

Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering. - Jin Peng Zhou; Ga Wu; Zheda Mai; Scott Sanner (CoRR, 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)

Online Class-Incremental Continual Learning with Adversarial Shapley Value. - Dongsub Shim; Zheda Mai; Jihwan Jeong; Scott Sanner; Hyunwoo Kim; Jongseong Jang (AAAI, 2021)

Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. - Zheda Mai; Ruiwen Li; Hyunwoo Kim; Scott Sanner (CVPR Workshops, 2021)

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 (SIGIR, 2022)

Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. - Tianshu Shen; Zheda Mai; Ga Wu; Scott Sanner (WWW, 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 001; Zheda Mai; David Vázquez 001; German Ignacio Parisi; Nikhil Churamani; et al. (Artif. Intell., 2022)

Unintended Bias in Language Model-driven Conversational Recommendation. - Tianshu Shen; Jiaru Li; Mohamed Reda Bouadjenek; Zheda Mai; Scott Sanner (CoRR, 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)

Online continual learning in image classification: An empirical survey. - Zheda Mai; Ruiwen Li; Jihwan Jeong; David Quispe; Hyunwoo Kim; Scott Sanner (Neurocomputing, 2022)

Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning. - Cheng-Hao Tu 001; Zheda Mai; Wei-Lun Chao (CVPR, 2023)

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. - Cheng-Hao Tu 001; Hong-You Chen; Zheda Mai; Jike Zhong; Vardaan Pahuja; Tanya Y. Berger-Wolf; Song Gao 001; Charles V. Stewart; Yu Su 001; Wei-Lun Chao (NeurIPS, 2023)

Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation. - Tianle Chen; Zheda Mai; Ruiwen Li; Wei-Lun Chao (CoRR, 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)

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., 2023)

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 (NeurIPS, 2024)

Fine-Tuning is Fine, if Calibrated. - Zheda Mai; Arpita Chowdhury; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Vardaan Pahuja; Tanya Y. Berger-Wolf; Song Gao 001; Charles V. Stewart; Yu Su 001; Wei-Lun Chao (NeurIPS, 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)

Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Transfer Learning (PETL) in Visual Recognition. - Zheda Mai; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Li Zhang 003; Wei-Lun Chao (CoRR, 2024)

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 001; et al. (CVPR, 2025)

Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition. - Zheda Mai; Ping Zhang 016; Cheng-Hao Tu 001; Hong-You Chen; Quang-Huy Nguyen; Li Zhang 003; Wei-Lun Chao (CVPR, 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 (CVPR Workshops, 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 001; Wei-Lun Chao (CVPR, 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 (ICASSP, 2025)

MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference. - Zhongwei Wan; Hui Shen; Xin Wang 120; Che Liu; Zheda Mai; Mi Zhang 002 (NAACL (Long Papers), 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 001; et al. (CoRR, 2025)

Revisiting semi-supervised learning in the era of foundation models. - Ping Zhang 016; Zheda Mai; Quang-Huy Nguyen; Wei-Lun Chao (CoRR, 2025)

BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning. - Jianyang Gu; Samuel Stevens 001; 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; et al. (CoRR, 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, 2025)