Papers by Rundong Gao

2 papers
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation? (2024.naacl-long)

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Challenge: Existing models for text-to-image generation have been underperforming in image-totext generation tasks.
Approach: They propose a framework that uses a split BERT to create a dedicated latent space for captions and integrates a regularization module to manage varying text lengths.
Outcome: The proposed framework achieves state-of-the-art performance on the MS COCO dataset with 38.2 BLEU@4 and 126.2 CIDEr .
Holistic Sentence Embeddings for Better Out-of-Distribution Detection (2022.findings-emnlp)

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Challenge: Pretrained language models have shown superior performance for textual OOD detection, but they estimate sample distance scores in the last-layer CLS embedding space.
Approach: They propose to use token averaging and layer combination to boost OOD detection by deriving more holistic sentence embeddings.
Outcome: The proposed method surpasses the state-of-the-art on a comprehensive suite of benchmarks by a 9.33% FAR95 margin.

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