Promises and Pitfalls of Black-Box Concept Learning Models

Promises and Pitfalls of Black-Box Concept Learning Models

24 June 2021

Finale Doshi-Velez

Papers citing "Promises and Pitfalls of Black-Box Concept Learning Models"

13 / 13 papers shown

Title
Concept-Based Unsupervised Domain Adaptation Xinyue Xu Y. Hu Hui Tang Yi Qin Lu Mi Hao Wang Xiaomeng Li 50 0 0 08 May 2025
Position: We need responsible, application-driven (RAD) AI research Sarah Hartman Cheng Soon Ong Julia Powles Petra Kuhnert 33 0 0 07 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 107 0 0 28 Apr 2025
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts M. Zarlenga Gabriele Dominici Pietro Barbiero Z. Shams M. Jamnik KELM 123 0 0 24 Apr 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 55 2 0 16 Feb 2025
VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance Divyansh Srivastava Beatriz Cabrero-Daniel Christian Berger VLM 57 8 0 17 Jan 2025
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models Nishad Singhi Jae Myung Kim Karsten Roth Zeynep Akata 40 1 0 02 May 2024
Understanding and Enhancing Robustness of Concept-based Models Sanchit Sinha Mengdi Huai Jianhui Sun Aidong Zhang AAML 21 18 0 29 Nov 2022
Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions J. Lockhart Daniele Magazzeni Manuela Veloso 9 4 0 21 Nov 2022
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Y. Zou 133 185 0 31 May 2022
Concept Embedding Analysis: A Review Gesina Schwalbe 19 28 0 25 Mar 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 17 25 0 25 Feb 2022
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 13 301 0 01 Nov 2021