Papers with encoder module

3 papers
A Novel Cascade Binary Tagging Framework for Relational Triple Extraction (2020.acl-main)

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Challenge: Existing approaches to extract relational triples from unstructured text are inadequate to solve the overlapping triple problem.
Approach: They propose a cascade binary tagging framework that models relations as functions that map subjects to objects in a sentence.
Outcome: The proposed framework outperforms state-of-the-art methods on two datasets . it outperformed baseline methods by 17.5 and 30.2 absolute gains .
On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (2021.findings-emnlp)

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Challenge: Experimental results show that PT and BT are nicely complementary to each other.
Approach: They introduce two probing tasks for PT and BT respectively and investigate their complementarity.
Outcome: The proposed methods establish state-of-the-art on the WMT16 English-Romanian and English-Russian benchmarks.
Uni-Dubbing: Zero-Shot Speech Synthesis from Visual Articulation (2024.acl-long)

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Challenge: Multimodal speech synthesis is a key challenge due to the scarcity of datasets that pair audio with corresponding video.
Approach: They propose a method that incorporates modality alignment during the pre-training phase on multimodal datasets and freezes the video modality extraction component and the encoder module within the pretrained weights.
Outcome: The proposed method achieves a reduced word error rate (WER) of 31.73%, surpassing the previous best of 33.9% with single-modality audio.

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