CLBench-V: Evaluating Multimodal Context Learning from Grounding to Knowledge Acquisition
Real-world tasks often require models to learn from task-specific context rather than relying only on pre-trained knowledge. While recent work has highlighted this capability as context learning, existing evaluations mainly focus on textual contexts. In many practical settings, however, the context to be learned from is multimodal: scientific findings are conveyed through figures and tables, financial indicators are scattered across converted reports, and spatial decisions depend on maps, scenes, or web pages. We introduce CLBench-V, a benchmark for multimodal context learning that addresses the difficulty of localizing where context use breaks down by organizing tasks around three dimens...
| Authors | Lai Wei, Chengqi Li, Jiapeng Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 28 July 2026 |
| Last updated at source | 28 July 2026 |
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