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TwinICL: Diagnosing Multimodal In-Context Learning through Paired Counterfactuals
In-context learning (ICL) enables models to infer tasks from demonstrations, but existing benchmarks generally lack matched text and image versions needed to compare ICL performance across modalities. We introduce TwinICL, a procedurally generated benchmark providing such pairs for controlled compar
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