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20212023
most citedHow Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness?

30 citations · 74 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV202325 cited

ChartLlama: A Multimodal LLM for Chart Understanding and Generation

Yucheng Han, Chi Zhang, Xin Chen +5

Multi-modal large language models have demonstrated impressive performances on most vision-language tasks. However, the model generally lacks the understanding capabilities for spe…

cs.CV20232 cited

Tuning Multi-mode Token-level Prompt Alignment across Modalities

Dongsheng Wang, Miaoge Li, Xinyang Liu +3

Advancements in prompt tuning of vision-language models have underscored their potential in enhancing open-world visual concept comprehension. However, prior works only primarily f…

cs.CV20231 cited

Invariant Feature Regularization for Fair Face Recognition

Jiali Ma, Zhongqi Yue, Kagaya Tomoyuki +4

Fair face recognition is all about learning invariant feature that generalizes to unseen faces in any demographic group. Unfortunately, face datasets inevitably capture the imbalan…

cs.CV2023

Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

Many studies focus on improving pretraining or developing new backbones in text-video retrieval. However, existing methods may suffer from the learning and inference bias issue, as…

cs.CV2023

An Overview of Challenges in Egocentric Text-Video Retrieval

Burak Satar, Hongyuan Zhu, Hanwang Zhang +1

Text-video retrieval contains various challenges, including biases coming from diverse sources. We highlight some of them supported by illustrations to open a discussion. Besides,…

cs.CV20233 cited

Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection

Hui Lv, Zhongqi Yue, Qianru Sun +3

Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the binary anomaly label is only given on the video level, but the output requires snippet-level prediction…