Papers with in-context learning LMMs
Selectively Answering Visual Questions (2024.findings-acl)
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| Challenge: | Large multi-modal models (LMMs) are capable of visual question answering (VQA) with unprecedented accuracy. |
| Approach: | They propose a calibration score that can be used to quantify uncertainty in visual question answering models. |
| Outcome: | The proposed calibration score is better calibrated than in text-only models for in-context learning. |