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ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models

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In the function of https://github.com/ExplainableML/ProbVLM/blob/cb69f28b1ab23142a1c671e004b09b5cb5d8a204/src/losses.py#L81, `nn.L1Loss` is inconsistent with Eq.3 in the paper, and Eq. 3 does not include the `nn.L1Loss`. Waiting for your help! @udion @sgk98

@udion @sgk98 Thank you. Could you provide the evaluation code, please? Is the following code for calculating uncertainty correct? ```python def mean(tensor): log_tensor = torch.log(tensor) mean_log = torch.mean(log_tensor) geometric_mean =...

Thank you for your wonderful paper, but I have a question about a formula: ![image](https://github.com/ExplainableML/ProbVLM/assets/55874332/196749bb-1b3b-4234-a3b2-d55a4d4a7402) In my understanding. If we ask for maximum likelihood, the parameters of the model have...

I would like to test the trained adapter model but I do not see any checkpoints unless I am missing something