Emanuele Marconato
3 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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GlanceNets: Interpretabile, Leak-proof Concept-based Models
2022 · arXiv (Cornell University)
There is growing interest in concept-based models (CBMs) that combine high-performance and interpretability by acquiring and reasoning with a vocabulary of high-level concepts. A key requirement is that the concepts be interpretable. Existing CBMs tackle …
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Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations
2023 · arXiv (Cornell University)
Neuro-symbolic predictors learn a mapping from sub-symbolic inputs to higher-level concepts and then carry out (probabilistic) logical inference on this intermediate representation. This setup offers clear advantages in terms of consistency to symbolic prior knowledge, …
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If Concept Bottleneck ARE THE QUESTION, ARE FOUNDATION MODELS THE ANSWER?
2025 · Zenodo (CERN European Organization for Nuclear Research)
Concept Bottleneck Models (CBMs) are neural networks designed to conjoin high performance withante-hoc interpretability. CBMs work by first mapping inputs (e.g., images) to high-level concepts(e.g., visible objects and their properties) and then use these to …