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  | Task | Type | Dataset | Non-LLM SoTA<sup>1</sup> | GPT-3.5<sup>2</sup> | GPT-4<sup>2</sup> | GPT-4o | Jellyfish-13B | Jellyfish-7B | Jellyfish-8B |
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  | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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- | Entity Matching | Seen | Fodors-Zagats | 100 | 100 | 100 | | 100 | 100 | 92.68 |
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  | Entity Matching | Seen | Beer | 94.37| 96.30 | 100 | | 96.77 | 96.55| 96.30 |
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  | Entity Matching | Seen | iTunes-Amazon | 97.06| 96.43 | 100 | | 98.11 | 96.30| 92.00 |
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  | Entity Matching | Seen | DBLP-ACM | 98.99| 96.99 | 97.44 | | 98.98 | 98.88| 98.76 |
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  | Entity Matching | Seen | DBLP-GoogleScholar | 95.60| 76.12 | 91.87 | | 98.51 | 95.15| 93.20 |
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- | Entity Matching | Seen | Amazon-Google | 75.58| 66.53 | 74.21 | | 81.34 | 80.83 | 74.49 |
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  | Entity Matching | Unseen | Walmart-Amazon | 86.76| 86.17 | 90.27 | | 89.42 | 85.64 | 89.97 |
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  | Entity Matching | Unseen | Abt-Buy | 89.33 | -- | 92.77 | | 89.58 | 82.38 | 92.54 |
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  | Data Imputation | Seen | Restaurant | 77.20| 94.19 | 97.67 | | 94.19 | 88.37 | 87.21 |
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  | Data Imputation | Seen | Buy | 96.50| 98.46 | 100 | | 100 | 96.62 | 92.31 |
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  | Data Imputation | Unseen | Filpkart | 68.00 | -- | 89.94 | | 81.68 | 79.44| 90.17 |
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  | Data Imputation | Unseen | Phone | 86.70| -- | 90.79 | | 87.21 | 85.00| 83.92 |
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- | Error Detection | Seen | Hosptial | 94.40| 90.74 | 90.74 | | 95.59 | 96.27 | 80.72|
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- | Error Detection | Seen | Adult | 99.10| 92.01 | 92.01 | | 99.33 | 91.96 | 81.72|
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- | Error Detection | Unseen | Flights | 81.00 | -- | 83.48 | | 82.52 | 66.92 | 75.18 |
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- | Error Detection | Unseen | Rayyan | 79.00| -- | 81.95 | | 90.65 | 69.82 | 91.54 |
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- | Schema Matching | Seen | Sythea | 38.50| 57.14 | 66.67 | | 36.36 | 44.44 | 27.27 |
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- | Schema Matching | Seen | MIMIC | 20.00| -- | 40.00 | | 40.00 | 40.00 | 34.04|
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- | Schema Matching | Unseen | CMS | 50.00| -- | 19.35 | | 59.29 | 13.79 | 56.72|
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  _For GPT-3.5 and GPT-4, we used the few-shot approach on all datasets. However, for Jellyfish-13B and Jellyfish-Interpreter, the few-shot approach is disabled on seen datasets and enabled on unseen datasets._
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  _Accuracy as the metric for data imputation and the F1 score for other tasks._
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  ## Performance on unseen tasks
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  ### Column Type Annotation
 
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  | Task | Type | Dataset | Non-LLM SoTA<sup>1</sup> | GPT-3.5<sup>2</sup> | GPT-4<sup>2</sup> | GPT-4o | Jellyfish-13B | Jellyfish-7B | Jellyfish-8B |
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  | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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+ | Entity Matching | Seen | Fodors-Zagats | 100 | 100 | 100 | | 100 | 100 | 92.68 |
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  | Entity Matching | Seen | Beer | 94.37| 96.30 | 100 | | 96.77 | 96.55| 96.30 |
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  | Entity Matching | Seen | iTunes-Amazon | 97.06| 96.43 | 100 | | 98.11 | 96.30| 92.00 |
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  | Entity Matching | Seen | DBLP-ACM | 98.99| 96.99 | 97.44 | | 98.98 | 98.88| 98.76 |
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  | Entity Matching | Seen | DBLP-GoogleScholar | 95.60| 76.12 | 91.87 | | 98.51 | 95.15| 93.20 |
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+ | Entity Matching | Seen | Amazon-Google | 75.58| 66.53 | 74.21 | 70.91 | 81.34 | 80.83 | 74.49 |
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  | Entity Matching | Unseen | Walmart-Amazon | 86.76| 86.17 | 90.27 | | 89.42 | 85.64 | 89.97 |
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  | Entity Matching | Unseen | Abt-Buy | 89.33 | -- | 92.77 | | 89.58 | 82.38 | 92.54 |
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  | Data Imputation | Seen | Restaurant | 77.20| 94.19 | 97.67 | | 94.19 | 88.37 | 87.21 |
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  | Data Imputation | Seen | Buy | 96.50| 98.46 | 100 | | 100 | 96.62 | 92.31 |
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  | Data Imputation | Unseen | Filpkart | 68.00 | -- | 89.94 | | 81.68 | 79.44| 90.17 |
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  | Data Imputation | Unseen | Phone | 86.70| -- | 90.79 | | 87.21 | 85.00| 83.92 |
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+ | Error Detection | Seen | Hosptial | 94.40| 90.74 | 90.74 | 44.76 | 95.59 | 96.27 | 80.72|
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+ | Error Detection | Seen | Adult | 99.10| 92.01 | 92.01 | 83.58 | 99.33 | 91.96 | 81.72|
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+ | Error Detection | Unseen | Flights | 81.00 | -- | 83.48 | 66.01 | 82.52 | 66.92 | 75.18 |
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+ | Error Detection | Unseen | Rayyan | 79.00| -- | 81.95 | 68.53 | 90.65 | 69.82 | 91.54 |
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+ | Schema Matching | Seen | Sythea | 38.50| 57.14 | 66.67 | 6.56 | 36.36 | 44.44 | 27.27 |
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+ | Schema Matching | Seen | MIMIC | 20.00| -- | 40.00 | 29.41 | 40.00 | 40.00 | 34.04|
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+ | Schema Matching | Unseen | CMS | 50.00| -- | 19.35 | 22.22 | 59.29 | 13.79 | 56.72|
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  _For GPT-3.5 and GPT-4, we used the few-shot approach on all datasets. However, for Jellyfish-13B and Jellyfish-Interpreter, the few-shot approach is disabled on seen datasets and enabled on unseen datasets._
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  _Accuracy as the metric for data imputation and the F1 score for other tasks._
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+ | Task | Type | Dataset | Best of non-LLM | GPT-3 | GPT-3.5 | GPT-4 | GPT-4o | Table-GPT | Jellyfish-7B | Jellyfish-8B | Jellyfish-13B |
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+ |------|--------|----------------------|-----------------|-------|---------|-------|--------|-----------|--------------|--------------|---------------|
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+ | Error Detection | Seen | Adult | *99.10 | 99.10 | 92.01 | 92.01 | 83.58 | -- | 77.40 | 73.74 | **99.33 |
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+ | | | Hospital | 94.40 | **97.80 | 90.74 | 90.74 | 44.76 | -- | 94.51 | 93.40 | *95.59 |
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+ | | Unseen | Flights | 81.00 | -- | -- | **83.48 | 66.01 | -- | 69.15 | 66.21 | *82.52 |
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+ | | | Rayyan | 79.00 | -- | -- | *81.95 | 68.53 | -- | 75.07 | 81.06 | **90.65 |
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+ | Data Imputation | Seen | Buy | 96.50 | 98.50 | 98.46 | **100 | **100 | -- | 98.46 | 98.46 | **100 |
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+ | | | Restaurant | 77.20 | 88.40 | *94.19 | **97.67 | 90.70 | -- | 89.53 | 87.21 | 89.53 |
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+ | | Unseen | Flipkart | 68.00 | -- | -- | **89.94 | 83.20 | -- | 87.14 | *87.48 | 81.68 |
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+ | | | Phone | 86.70 | -- | -- | **90.79 | 86.78 | -- | 86.52 | 85.68 | *87.21 |
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+ | Schema Matching | Seen | MIMIC-III | 20.00 | -- | -- | 40.00 | 29.41 | -- | **53.33 | *45.45 | 40.00 |
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+ | | | Synthea | 38.50 | 45.20 | *57.14 | **66.67 | 6.56 | -- | 55.56 | 47.06 | 56.00 |
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+ | | Unseen | CMS | *50.00 | -- | -- | 19.35 | 22.22 | -- | 42.86 | 38.10 | **59.29 |
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+ | Entity Matching | Seen | Amazon-Google | 75.58 | 63.50 | 66.50 | 74.21 | 70.91 | 70.10 | **81.69 | *81.42 | 81.34 |
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+ | | | Beer | 94.37 | **100 | 96.30 | **100 | 90.32 | 96.30 | **100.00 | **100.00 | 96.77 |
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+ | | | DBLP-ACM | **98.99 | 96.60 | 96.99 | 97.44 | 95.87 | 93.80 | 98.65 | 98.77 | *98.98 |
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+ | | | DBLP-GoogleScholar | *95.70 | 83.80 | 76.12 | 91.87 | 90.45 | 92.40 | 94.88 | 95.03 | **98.51 |
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+ | | | Fodors-Zagats | **100 | **100 | **100 | **100 | 93.62 | **100 | **100 | **100 | **100 |
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+ | | | iTunes-Amazon | 97.06 | *98.20 | 96.40 | **100 | 98.18 | 94.30 | 96.30 | 96.30 | 98.11 |
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+ | | Unseen | Abt-Buy | 89.33 | -- | -- | **92.77 | 78.73 | -- | 86.06 | 88.84 | *89.58 |
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+ | | | Walmart-Amazon | 86.89 | 87.00 | 86.17 | **90.27 | 79.19 | 82.40 | 84.91 | 85.24 | *89.42 |
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+ | Avg | | | 80.44 | - | - | *84.17 | 72.58 | - | 82.74 | 81.55 | **86.02 |
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  ## Performance on unseen tasks
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  ### Column Type Annotation