Papers by Fengzong Lian

2 papers
LightVLP: A Lightweight Vision-Language Pre-training via Gated Interactive Masked AutoEncoders (2024.lrec-main)

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Challenge: Existing vision-language pre-training models use multi-modal encoders to encode image and text, causing noisy training corpora.
Approach: They propose a vision-language pre-training framework with two autoencoders for efficient training . they propose masked tokens and a gated interaction mechanism to cope with noise .
Outcome: The proposed model achieves 2.2% R@1 gains on COCO Text Retrieval and 1.1% on refCOCO+ on six datasets.
An Anchor-based Relative Position Embedding Method for Cross-Modal Tasks (2022.emnlp-main)

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Challenge: Position Embedding (PE) is essential for transformer to capture the sequence ordering of input tokens.
Approach: They propose a unified position embedding method that bridges the semantic gap between modalities and embeds the anchor-based distance to guide computation of cross-attention.
Outcome: The proposed method obtains new SOTA results on a wide range of benchmarks.

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