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Update the Applications section in the paper’s MDX files for all 13 languages with the Element-to-Tuple Prompting paper.
The added paper ('Element to Tuple Prompting') is an enhanced and improved version of the paper titled 'MvP: Multi-View Prompting Improves Aspect Sentiment Tuple Prediction', which was previously listed in the Applications section of the papers.en.mdx file.
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@@ -181,6 +181,7 @@ Die folgenden sind die neuesten Papers (sortiert nach Veröffentlichungsdatum) z
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## Anwendungen
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-[E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple Prediction](https://arxiv.org/pdf/2405.06454) (May 2024)
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-[PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming](https://arxiv.org/abs/2310.09265) (Oktober 2023)
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-[Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation](https://arxiv.org/abs/2310.08395) (Oktober 2023)
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-[Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification](https://arxiv.org/abs/2310.08123) (Oktober 2023)
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@@ -185,6 +185,7 @@ The following are the latest papers (sorted by release date) on prompt engineeri
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## Applications
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-[E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple Prediction](https://arxiv.org/pdf/2405.06454) (May 2024)
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-[PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming](https://arxiv.org/abs/2310.09265) (October 2023)
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-[Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation](https://arxiv.org/abs/2310.08395) (October 2023)
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-[Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification](https://arxiv.org/abs/2310.08123) (October 2023)
-[Automated Reading Passage Generation with OpenAI's Large Language Model](https://arxiv.org/abs/2304.04616) (April 2023)
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-[WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web Corpus](https://arxiv.org/abs/2304.04358) (April 2023)
-[Automated Reading Passage Generation with OpenAI's Large Language Model](https://arxiv.org/abs/2304.04616) (April 2023)
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-[WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web Corpus](https://arxiv.org/abs/2304.04358) (April 2023)
-[BloombergGPT: A Large Language Model for Finance](https://arxiv.org/abs/2303.17564) (March 2023)
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-[Medical Intervention Duration Estimation Using Language-enhanced Transformer Encoder with Medical Prompts](https://arxiv.org/abs/2303.17408) (March 2023)
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@@ -185,6 +185,7 @@ A seguir estão os artigos mais recentes (classificados por data de lançamento)
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## Aplicações
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-[E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple Prediction](https://arxiv.org/pdf/2405.06454) (May 2024)
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-[PromptRE: Weakly-Supervised Document-Level Relation Extraction via Prompting-Based Data Programming](https://arxiv.org/abs/2310.09265) (October 2023)
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-[Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation](https://arxiv.org/abs/2310.08395) (October 2023)
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-[Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification](https://arxiv.org/abs/2310.08123) (October 2023)
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