Papers by Chuanhao Lv

2 papers
Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs (2023.findings-emnlp)

Copied to clipboard

Challenge: Existing studies show that multimodal machine translation systems exhibit decreased sensitivity to visual information when text inputs are complete.
Approach: They propose to generate parallel VQA style pairs from source text to foster more robust cross-modal interaction.
Outcome: The proposed approach generates parallel VQA style pairs from the source text, fostering more robust cross-modal interaction.
On Vision Features in Multimodal Machine Translation (2022.acl-long)

Copied to clipboard

Challenge: Recent work on multimodal machine translation (MMT) has focused on the way of incorporating vision features into translation but little attention is given to the quality of vision models.
Approach: They develop a selective attention model to study the patch-level contribution of an image in multimodal machine translation.
Outcome: The proposed model is able to learn translation from the visual modality on probing tasks and is compared with existing models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations