Papers with BLEU-4 score

3 papers
Video-guided Machine Translation with Spatial Hierarchical Attention Network (2021.acl-srw)

Copied to clipboard

Challenge: Existing studies use pretrained motion detection models as verb sense ambiguity representations to solve the verb sense problem.
Approach: They propose to use video contents as auxiliary information to address the word sense ambiguity problem in machine translation.
Outcome: Experiments on the VATEX dataset show that the proposed system achieves 35.86 BLEU-4 score, which is 0.51 score higher than the single model of the SOTA method.
BrainECHO: Semantic Brain Signal Decoding through Vector-Quantized Spectrogram Reconstruction for Whisper-Enhanced Text Generation (2025.findings-acl)

Copied to clipboard

Challenge: Current EEG/MEG-to-text decoding systems rely on teacher-forcing methods . pre-trained large language models are over-dominant in decoding text from brain activity .
Approach: They propose a framework that employs decoupled representation learning to achieve state-of-the-art performance on EEG and MEG datasets.
Outcome: The proposed framework achieves state-of-the-art performance on EEG and MEG datasets.
Sign Language Production With Avatar Layering: A Critical Use Case over Rare Words (2022.lrec-1)

Copied to clipboard

Challenge: Existing vision-based sign language production approaches suffer from out-of-vocabulary (OOV) and test-time generalization problems.
Approach: They propose an avatar-based sign language production system that generates sign language videos from spoken language expressions.
Outcome: The proposed system achieves higher BLEU-4 and higher ROUGE-L scores on a new Korean-Korean sign language dataset.

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