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Found 3 papers, 1 papers with code
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models
In this paper, we find that this is noticeably driven by an independent treatment of concepts during intervention, wherein a change of one concept does not influence the use of other ones in the model's final decision.
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
Multimodal contrastive pretraining has been used to train multimodal representation models, such as CLIP, on large amounts of paired image-text data.
Toward a normative theory of (self-)management by goal-setting
This creates an untapped opportunity to derive practical recommendations for which subgoals managers and individuals should set from cognitive models of bounded rationality.
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