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Found 6 papers, 1 papers with code
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models
Abstractive summarization models often generate factually inconsistent content particularly when the parametric knowledge of the model conflicts with the knowledge in the input document.
AligNART: Non-autoregressive Neural Machine Translation by Jointly Learning to Estimate Alignment and Translate
Non-autoregressive neural machine translation (NART) models suffer from the multi-modality problem which causes translation inconsistency such as token repetition.
Rare Tokens Degenerate All Tokens: Improving Neural Text Generation via Adaptive Gradient Gating for Rare Token Embeddings
AGG addresses the degeneration problem by gating the specific part of the gradient for rare token embeddings.
FloWaveNet : A Generative Flow for Raw Audio
Most of modern text-to-speech architectures use a WaveNet vocoder for synthesizing a high-fidelity waveform audio, but there has been a limitation for practical applications due to its slow autoregressive sampling scheme.
Sound Audio and Speech Processing
Deep Learning on Key Performance Indicators for Predictive Maintenance in SAP HANA
The experimental results with real-world data confirm the effectiveness of the system and models.
Building a Neural Machine Translation System Using Only Synthetic Parallel Data
Experiments on Czech-German and French-German translations demonstrate the efficacy of the proposed pseudo parallel corpus, which shows not only enhanced results for bidirectional translation tasks but also substantial improvement with the aid of a ground truth real parallel corpus.
