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### Title
Cross-lingual Contextualized Topic Models with Zero-shot Learning.
### Team Name
TeamTatakae
### Email
202318024@daiict.ac.in
### Team Member 1 Name
Mitul Dudhat
### …
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I am encountering a ```FloatingPointError``` between steps 43K and 48K while training the LGR-SMoE model on the OPUS-100 dataset for a total of 200K steps. The issue halts the training process, and I'…
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文字中如果有空格会抛异常:
"现在删除 API 只需要一个书籍 ID"
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Reading the paper on multisimlex, I realized that there is some tradition to these datasets, although they are small and have nothing to do with historical linguistics or psychology: http://lcl.unirom…
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Perform a similar study to https://arxiv.org/pdf/1907.04307.pdf
but expanding to support 100 languages using the [embeddings from the translator](https://github.com/artitw/text2text#embedding--vector…
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'generator' object is not subscriptable
prompt_audio = (prompt_speech.numpy() * (2 ** 15)).astype(np.int16).tobytes()
prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(prompt_aud…
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## 一言でいうと
多言語対応の文表現を得る際、どんなタスクが良いのか検証した研究。ベースは言語モデルで、通常通り次の単語を予測する(Causal LM)、単語をdropした箇所を予測する(Masked LM)＋翻訳データがある場合に、並べた文でMasked LMを行うTranslation LMの計3つを提案。CLM
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abstract
最近的很多研究展示了multi-lingual bert的跨语言性能，因为其是在没有任何跨语言目标和对齐数据的情况下训练的。本工作中，我们提供了一个综合的调研——M-BERT不同组件对于其跨语言能力的贡献。我们研究语言属性、模型结构和学习目标的影响。我们的实验研究三种不同类型的语言(西班牙语，印地语，俄语)和两个不同概念的NLP任务（文本蕴含和命名实体识别）。我们主要结论发…
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Hi Nils Reimers,
Thank you for your great job,
I want to ask you if Cross encore can be applied to Multi-language or not?
Specifically I want to apply the simimarity text for French is it good?
Th…
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Hello,
Thank you for your comprehensive and wonderful survey.
Would you mind adding 2 papers about text summarization?
Paper 1: Enriching and Controlling Global Semantics for Text Summarizati…