Papers with feedforward neural network

2 papers
OpenSubtitles2018: Statistical Rescoring of Sentence Alignments in Large, Noisy Parallel Corpora (L18-1)

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Challenge: Movie and TV subtitles are a valuable resource for the compilation of parallel corpora . however, the quality of the resulting sentence alignments is often lower than for other parallel corpoora.
Approach: They propose to use movie and TV subtitles to extract parallel corpora from 3.7 million subtitles spread over 60 languages to obtain explicit quality scores for each sentence alignment.
Outcome: The proposed model predicts translation probabilities with a root mean square error of 0.07 . the results show that the model can prune out low-quality alignments .
FreeCtrl: Constructing Control Centers with Feedforward Layers for Learning-Free Controllable Text Generation (2024.acl-long)

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Challenge: Controllable text generation (CTG) focuses on crafting texts adhering to specific attributes . studies show learning-based methods require extensive computational and data resources .
Approach: They propose a learning-free approach that dynamically adjusts the weights of selected feedforward neural network vectors to steer the outputs of large language models.
Outcome: The proposed approach outperforms learning-based and learning-free methods on multi-attribute control.

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