Scale Alone Does not Improve Mechanistic Interpretability in Vision
Models

Scale Alone Does not Improve Mechanistic Interpretability in Vision Models

11 July 2023

Roland S. Zimmermann

Wieland Brendel

Papers citing "Scale Alone Does not Improve Mechanistic Interpretability in Vision Models"

10 / 10 papers shown

Title
Discovering Influential Neuron Path in Vision Transformers Yifan Wang Yifei Liu Yingdong Shi C. Li Anqi Pang Sibei Yang Jingyi Yu Kan Ren ViT 69 0 0 12 Mar 2025
Linear Explanations for Individual Neurons Tuomas P. Oikarinen Tsui-Wei Weng FAtt MILM 29 5 0 10 May 2024
Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIP Vedant Palit Rohan Pandey Aryaman Arora Paul Pu Liang 24 20 0 27 Aug 2023
Toy Models of Superposition Nelson Elhage Tristan Hume Catherine Olsson Nicholas Schiefer T. Henighan ... Sam McCandlish Jared Kaplan Dario Amodei Martin Wattenberg C. Olah AAML MILM 120 316 0 21 Sep 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 58 114 0 06 Dec 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,424 0 23 Jan 2020
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 52 116 0 07 Jun 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,672 0 28 Feb 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,237 0 25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,170 0 01 Sep 2014