Exploring a Pre-trained Model for Re-Matching News Texts and Images. - Mingliang Liang; Martha A. Larson (MediaEval, 2021)

Textual Concept Expansion for Text-Image Matching within Online News Content. - Mingliang Liang; Martha A. Larson (MediaEval, 2022)

NewsImages: addressing the depiction gap with an online news dataset for text-image rematching. - Andreas Lommatzsch; Benjamin Kille; Özlem Özgöbek; Yuxiao Zhou 002; Jelena Tesic; Cláudio Bartolomeu; David Semedo; Lidia Pivovarova; Mingliang Liang; Martha A. Larson (MMSys, 2022)

Subsampling of Frequent Words in Text for Pre-training a Vision-Language Model. - Mingliang Liang; Martha A. Larson (LGM3A@MM, 2023)

Investigating the Performance of the CLIP Model and Concept Matching in Text-Image Retrieval Systems. - Xiaomeng Wang; Mingliang Liang; Martha A. Larson (MediaEval, 2023)

Textual Concept Expansion with Commonsense Knowledge to Improve Dual-Stream Image-Text Matching. - Mingliang Liang; Zhuoran Liu 001; Martha A. Larson (MMM (1), 2023)

Mutant Texts: A Technique for Uncovering Unexpected Inconsistencies in Large-Scale Vision-Language Models. - Mingliang Liang; Zhouran Liu; Martha A. Larson (MMM (4), 2024)

Centered Masking for Language-Image Pre-training. - Mingliang Liang; Martha A. Larson (ECML/PKDD (8), 2024)

Enhancing Vision-Language Model Pre-training with Image-text Pair Pruning Based on Word Frequency. - Mingliang Liang; Martha A. Larson (CoRR, 2024)

Frequency Is What You Need: Word-frequency Masking Benefits Vision-Language Model Pre-training. - Mingliang Liang; Martha A. Larson (CoRR, 2024)