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@@ -468,7 +468,7 @@ configs:
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  # LlamaLens: Specialized Multilingual LLM Dataset
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  ## Overview
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- LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 19 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi.
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  <p align="center"> <img src="./capablities_tasks_datasets.png" style="width: 40%;" id="title-icon"> </p>
@@ -523,35 +523,35 @@ calculated as **(LLamalens – SOTA)**.
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  ---
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- | **Task** | **Dataset** | **Metric** | **SOTA** | **Llama3.1-instruct** | **Llamalens-English** | **Δ (LLamalens SOTA)** |
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- |:-----------------------------:|:----------------------------------:|:----------:|:--------:|:---------------------:|:---------------------:|--------------------------|
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- | Attentionworthiness Detection | CT22Attentionworthy | W-F1 | 0.412 | 0.158 | 0.425 | 0.013 |
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- | Checkworthiness Detection | CT24_checkworthy | F1_Pos | 0.569 | 0.610 | 0.502 | -0.067 |
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- | Claim Detection | CT22Claim | Acc | 0.703 | 0.581 | 0.734 | 0.031 |
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- | Cyberbullying Detection | ArCyc_CB | Acc | 0.863 | 0.766 | 0.870 | 0.007 |
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- | Emotion Detection | Emotional-Tone | W-F1 | 0.658 | 0.358 | 0.705 | 0.047 |
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- | Emotion Detection | NewsHeadline | Acc | 1.000 | 0.406 | 0.480 | -0.520 |
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- | Factuality | Arafacts | Mi-F1 | 0.850 | 0.210 | 0.771 | -0.079 |
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- | Factuality | COVID19Factuality | W-F1 | 0.831 | 0.492 | 0.800 | -0.031 |
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- | Harmfulness Detection | CT22Harmful | F1_Pos | 0.557 | 0.507 | 0.523 | -0.034 |
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- | Hate Speech Detection | annotated-hatetweets-4-classes | W-F1 | 0.630 | 0.257 | 0.526 | -0.104 |
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- | Hate Speech Detection | OSACT4SubtaskB | Mi-F1 | 0.950 | 0.819 | 0.955 | 0.005 |
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- | News Categorization | ASND | Ma-F1 | 0.770 | 0.587 | 0.919 | 0.149 |
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- | News Categorization | SANADAkhbarona-news-categorization | Acc | 0.940 | 0.784 | 0.954 | 0.014 |
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- | News Categorization | SANADAlArabiya-news-categorization | Acc | 0.974 | 0.893 | 0.987 | 0.013 |
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- | News Categorization | SANADAlkhaleej-news-categorization | Acc | 0.986 | 0.865 | 0.984 | -0.002 |
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- | News Categorization | UltimateDataset | Ma-F1 | 0.970 | 0.376 | 0.865 | -0.105 |
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- | News Credibility | NewsCredibilityDataset | Acc | 0.899 | 0.455 | 0.935 | 0.036 |
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- | News Summarization | xlsum | R-2 | 0.137 | 0.034 | 0.129 | -0.009 |
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- | Offensive Language Detection | ArCyc_OFF | Ma-F1 | 0.878 | 0.489 | 0.877 | -0.001 |
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- | Offensive Language Detection | OSACT4SubtaskA | Ma-F1 | 0.905 | 0.782 | 0.896 | -0.009 |
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- | Propaganda Detection | ArPro | Mi-F1 | 0.767 | 0.597 | 0.747 | -0.020 |
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- | Sarcasm Detection | ArSarcasm-v2 | F1_Pos | 0.584 | 0.477 | 0.520 | -0.064 |
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- | Sentiment Classification | ar_reviews_100k | F1_Pos | -- | 0.681 | 0.785 | -- |
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- | Sentiment Classification | ArSAS | Acc | 0.920 | 0.603 | 0.800 | -0.120 |
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- | Stance Detection | stance | Ma-F1 | 0.767 | 0.608 | 0.926 | 0.159 |
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- | Stance Detection | Mawqif-Arabic-Stance-main | Ma-F1 | 0.789 | 0.764 | 0.853 | 0.065 |
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- | Subjectivity Detection | ThatiAR | f1_pos | 0.800 | 0.562 | 0.441 | -0.359 |
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  ## File Format
 
468
  # LlamaLens: Specialized Multilingual LLM Dataset
469
 
470
  ## Overview
471
+ LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 18 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi.
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473
 
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  <p align="center"> <img src="./capablities_tasks_datasets.png" style="width: 40%;" id="title-icon"> </p>
 
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  ---
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+ | **Task** | **Dataset** | **Metric** | **SOTA** | **Llama3.1-instruct** | **Llamalens-English** | **Δ (LLamalens - SOTA)** |
527
+ |:-----------------------------:|:----------------------------------:|:----------:|:--------:|:---------------------:|:---------------------:|:------------------------:|
528
+ | Attentionworthiness Detection | CT22Attentionworthy | W-F1 | 0.412 | 0.158 | 0.425 | 0.013 |
529
+ | Checkworthiness Detection | CT24_checkworthy | F1_Pos | 0.569 | 0.610 | 0.502 | -0.067 |
530
+ | Claim Detection | CT22Claim | Acc | 0.703 | 0.581 | 0.734 | 0.031 |
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+ | Cyberbullying Detection | ArCyc_CB | Acc | 0.863 | 0.766 | 0.870 | 0.007 |
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+ | Emotion Detection | Emotional-Tone | W-F1 | 0.658 | 0.358 | 0.705 | 0.047 |
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+ | Emotion Detection | NewsHeadline | Acc | 1.000 | 0.406 | 0.480 | -0.520 |
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+ | Factuality | Arafacts | Mi-F1 | 0.850 | 0.210 | 0.771 | -0.079 |
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+ | Factuality | COVID19Factuality | W-F1 | 0.831 | 0.492 | 0.800 | -0.031 |
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+ | Harmfulness Detection | CT22Harmful | F1_Pos | 0.557 | 0.507 | 0.523 | -0.034 |
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+ | Hate Speech Detection | annotated-hatetweets-4-classes | W-F1 | 0.630 | 0.257 | 0.526 | -0.104 |
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+ | Hate Speech Detection | OSACT4SubtaskB | Mi-F1 | 0.950 | 0.819 | 0.955 | 0.005 |
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+ | News Categorization | ASND | Ma-F1 | 0.770 | 0.587 | 0.919 | 0.149 |
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+ | News Categorization | SANADAkhbarona-news-categorization | Acc | 0.940 | 0.784 | 0.954 | 0.014 |
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+ | News Categorization | SANADAlArabiya-news-categorization | Acc | 0.974 | 0.893 | 0.987 | 0.013 |
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+ | News Categorization | SANADAlkhaleej-news-categorization | Acc | 0.986 | 0.865 | 0.984 | -0.002 |
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+ | News Categorization | UltimateDataset | Ma-F1 | 0.970 | 0.376 | 0.865 | -0.105 |
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+ | News Credibility | NewsCredibilityDataset | Acc | 0.899 | 0.455 | 0.935 | 0.036 |
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+ | News Summarization | xlsum | R-2 | 0.137 | 0.034 | 0.129 | -0.009 |
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+ | Offensive Language Detection | ArCyc_OFF | Ma-F1 | 0.878 | 0.489 | 0.877 | -0.001 |
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+ | Offensive Language Detection | OSACT4SubtaskA | Ma-F1 | 0.905 | 0.782 | 0.896 | -0.009 |
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+ | Propaganda Detection | ArPro | Mi-F1 | 0.767 | 0.597 | 0.747 | -0.020 |
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+ | Sarcasm Detection | ArSarcasm-v2 | F1_Pos | 0.584 | 0.477 | 0.520 | -0.064 |
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+ | Sentiment Classification | ar_reviews_100k | F1_Pos | -- | 0.681 | 0.785 | -- |
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+ | Sentiment Classification | ArSAS | Acc | 0.920 | 0.603 | 0.800 | -0.120 |
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+ | Stance Detection | stance | Ma-F1 | 0.767 | 0.608 | 0.926 | 0.159 |
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+ | Stance Detection | Mawqif-Arabic-Stance-main | Ma-F1 | 0.789 | 0.764 | 0.853 | 0.065 |
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+ | Subjectivity Detection | ThatiAR | f1_pos | 0.800 | 0.562 | 0.441 | -0.359 |
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  ## File Format