Language benchmarks (overall).

Aggregated metric computed by the paper authors representing the overall averaged performance across multiple language benchmarks listed in Table 11. This is not a standalone dataset of examples; rather it is a summary score (an aggregate evaluation) computed from a collection of language-task benchmark results reported in the paper. It represents an overall language evaluation across many language benchmarks (average across the listed language tasks).

Best published scores.

No results indexed yet — be the first to submit a score.

Neighbouring benchmarks.

Other Few-Shot Image Classification datasets on Codesota.

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this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

• 01A public checkpoint or API endpoint
• 02A reproduction script with frozen commit + seed
• 03Declared evaluation environment (Python, deps)
• 04One row per metric declared by this dataset
• 05A contact so we can follow up on discrepancies