Papers by Wenping Ma

3 papers
Zero-Shot Cross-Lingual Transfer of Neural Machine Translation with Multilingual Pretrained Encoders (2021.emnlp-main)

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Challenge: Existing work on improving cross-lingual transferability of NMT model is under-explored.
Approach: They propose a model that leverages a multilingual pretrained encoder to improve cross-lingual transferability.
Outcome: The proposed model outperforms mBART and m2m-100 on a zero-shot cross-lingual transfer task.
Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine Translation (2022.acl-long)

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Challenge: Existing unsupervised neural machine translation systems can degrade when labeled data is limited.
Approach: They propose a multilingual pretraining and multilingual fine-tuning for facilitating cross-lingual transfer in zero-shot translation using a parallel dataset.
Outcome: The proposed model outperforms state-of-the-art models on many-to-English translation by over 7.2 and 5.0 BLEU.
ShredBench: Evaluating the Semantic Reasoning Capabilities of Multimodal LLMs in Document Reconstruction (2026.findings-acl)

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Challenge: Empirical evaluations on state-of-the-art MLLMs reveal a significant performance gap . ML models lack the fine-grained cross-modal reasoning required to bridge visual discontinuities.
Approach: They propose a benchmark that renders fragmented documents directly from Markdown to facilitate evaluation of VRDU tasks.
Outcome: The proposed benchmark renders fragmented documents directly from Markdown.

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