mBART
PulseAugur coverage of mBART — every cluster mentioning mBART across labs, papers, and developer communities, ranked by signal.
2 天有情绪数据
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Direct sign language translation model developed using synthetic data
Researchers have developed a novel method for direct translation between different sign languages, addressing a gap in current sign language technology. Their approach utilizes back-translation to create synthetic paral…
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Encoder-decoder transformers advance constituent parsing accuracy
研究人员探索了使用预训练的编码器-解码器 Transformer 模型进行句法成分分析，这是自然语言理解的关键任务。他们的工作通过对 BART、mBART 和 T5 等模型进行微调以生成线性化解析树，扩展了现有的序列到序列方法。研究表明，与专用解析器相比，该方法取得了有竞争力的结果，并且在连续解析任务上超越了之前的序列到序列模型。
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New dataset and benchmark advance Bangla text-to-gloss translation for BdSL
Researchers have developed the first dataset and benchmark for Bangla text-to-gloss translation, addressing a significant gap for the Bangla Sign Language (BdSL) community. The dataset includes manually annotated and sy…
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New study benchmarks machine transliteration models for Tajik-Farsi languages
This paper introduces a new benchmark for machine transliteration between Tajik and Farsi, developing a unique parallel corpus from diverse sources. The study compares six model architectures, including rule-based syste…
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CRAFT method speeds up training data selection for sequence-to-sequence models
Researchers have developed a new method called CRAFT (Clustered Regression for Adaptive Filtering of Training data) to efficiently select high-quality subsets of training data for sequence-to-sequence models. This appro…