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contextual_refinement_ende

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skoneru commited on Oct 17, 2023

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@@ -13,4 +13,4 @@ We provide three different type of examples covering contextual phenomena such a
  -  **Formality (Example 3 & 4):** The word "you" in English can be translated to German as Sie (Formal) and Du (Informal). The sentence-level model outputs are inconsistent and use both levels. However, you see that the LLM outputs are only formal. If you want it to be informal, you can change the formality level of the first translation and then let the model generate from that point.
  - **Pronouns (Example 5 & 6):** Here, the translation of it is unknown from the sentence alone and can be "Er", "Es" and "Sie" depending on the gender. Since, it is refering to garland, the right choice is Er. However, the LLM mistranslates the garland into "Krone" and uses "Sie" as the pronoun. However, once you fix the mistake and replace "Krone" with "Kränz", LLM refines the translation and use the right pronoun!
-![](file/process.png)

  -  **Formality (Example 3 & 4):** The word "you" in English can be translated to German as Sie (Formal) and Du (Informal). The sentence-level model outputs are inconsistent and use both levels. However, you see that the LLM outputs are only formal. If you want it to be informal, you can change the formality level of the first translation and then let the model generate from that point.
  - **Pronouns (Example 5 & 6):** Here, the translation of it is unknown from the sentence alone and can be "Er", "Es" and "Sie" depending on the gender. Since, it is refering to garland, the right choice is Er. However, the LLM mistranslates the garland into "Krone" and uses "Sie" as the pronoun. However, once you fix the mistake and replace "Krone" with "Kränz", LLM refines the translation and use the right pronoun!
+<img alt="" src="file/process.png" style="mix-blend-mode: multiply;">