most citedCross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval

43 citations · 48 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024

LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning

Fanshuang Kong, Richong Zhang, Ziqiao Wang

Hierarchical text classification (HTC) aims to assign one or more labels in the hierarchy for each text. Many methods represent this structure as a global hierarchy, leading to red…

stat.ML2024

Generalization Bounds via Conditional -Information

Ziqiao Wang, Yongyi Mao

In this work, we introduce novel information-theoretic generalization bounds using the conditional -information framework, an extension of the traditional conditional mutual inf…

cs.CL2024

Activated Parameter Locating via Causal Intervention for Model Merging

Fanshuang Kong, Richong Zhang, Ziqiao Wang

Model merging combines multiple homologous models into one model, achieving convincing generalization without the necessity of additional training. A key challenge in this problem…

cs.CV202443 cited

Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval

Hailang Huang, Zhijie Nie, Ziqiao Wang +1

Current image-text retrieval methods have demonstrated impressive performance in recent years. However, they still face two problems: the inter-modal matching missing problem and t…

stat.ML2023

Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds

Ziqiao Wang, Yongyi Mao

We present new information-theoretic generalization guarantees through the a novel construction of the "neighboring-hypothesis" matrix and a new family of stability notions termed…

cs.LG20232 cited

Over-training with Mixup May Hurt Generalization

Zixuan Liu, Ziqiao Wang, Hongyu Guo +1

Mixup, which creates synthetic training instances by linearly interpolating random sample pairs, is a simple and yet effective regularization technique to boost the performance of…