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most citedChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey

20 citations · 23 across the 13 of their papers we have counts for

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cs.CV20261 cited

iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data

Al Zadid Sultan Bin Habib, Md Younus Ahamed, Prashnna Gyawali +2

Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalization problems. To tackle this ch…

cs.CV2026

Naming the Concepts Classifiers Rely On: Language-Anchored Decomposition for Faithful Explanation

Ahsan Habib Akash, Dipkamal Bhusal, Stacey Jones +3

Deep neural networks are widely deployed in high-stakes visual applications where interpretability is critical, yet existing explanations face a trade-off: post-hoc concept methods…

cs.CV20241 cited

Rethinking Self-Supervised Learning Within the Framework of Partial Information Decomposition

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

Self Supervised learning (SSL) has demonstrated its effectiveness in feature learning from unlabeled data. Regarding this success, there have been some arguments on the role that m…

cs.CV2024

Direct Coloring for Self-Supervised Enhanced Feature Decoupling

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

The success of self-supervised learning (SSL) has been the focus of multiple recent theoretical and empirical studies, including the role of data augmentation (in feature decouplin…

cs.CV2024

FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation

Trong Thang Pham, Ngoc-Vuong Ho, Nhat-Tan Bui +8

Developing an interpretable system for generating reports in chest X-ray (CXR) analysis is becoming increasingly crucial in Computer-aided Diagnosis (CAD) systems, enabling radiolo…

cs.CV20231 cited

ZEETAD: Adapting Pretrained Vision-Language Model for Zero-Shot End-to-End Temporal Action Detection

Thinh Phan, Khoa Vo, Duy Le +3

Temporal action detection (TAD) involves the localization and classification of action instances within untrimmed videos. While standard TAD follows fully supervised learning with…