Representer Point Selection for Explaining Deep Neural Networks

23 November 2018

Papers citing "Representer Point Selection for Explaining Deep Neural Networks"

50 / 59 papers shown

Title
Federated learning, ethics, and the double black box problem in medical AI Joshua Hatherley Anders Søgaard Angela Ballantyne Ruben Pauwels FedML 58 0 0 29 Apr 2025
Image Interpolation with Score-based Riemannian Metrics of Diffusion Models Shinnosuke Saito Takashi Matsubara DiffM 82 1 0 28 Apr 2025
Most Influential Subset Selection: Challenges, Promises, and Beyond Yuzheng Hu Pingbang Hu Han Zhao Jiaqi W. Ma TDI 142 2 0 10 Jan 2025
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models Jinxu Lin Linwei Tao Minjing Dong Chang Xu TDI 44 2 0 24 Oct 2024
Data Quality Control in Federated Instruction-tuning of Large Language Models Yaxin Du Guangyi Liu Fengting Yuchi W. Zhao Jingjing Qu Yanjie Wang Siheng Chen ALM FedML 56 0 0 15 Oct 2024
$$\texttt{dattri}$: A Library for Efficient Data Attribution$ $\texttt{dattri}$ : A Library for Efficient Data Attribution Junwei Deng Ting-Wei Li Shiyuan Zhang Shixuan Liu Yijun Pan Hao Huang Xinhe Wang Pingbang Hu Xingjian Zhang Jiaqi W. Ma TDI 42 3 0 06 Oct 2024
Influence-oriented Personalized Federated Learning Yue Tan Guodong Long Jing Jiang Chengqi Zhang FedML 35 0 0 04 Oct 2024
Efficient Ensembles Improve Training Data Attribution Junwei Deng Ting-Wei Li Shichang Zhang Jiaqi Ma TDI 35 2 0 27 May 2024
Data-centric Prediction Explanation via Kernelized Stein Discrepancy Mahtab Sarvmaili Hassan Sajjad Ga Wu 36 1 0 22 Mar 2024
I-CEE: Tailoring Explanations of Image Classification Models to User Expertise Yao Rong Peizhu Qian Vaibhav Unhelkar Enkelejda Kasneci 34 0 0 19 Dec 2023
Intriguing Properties of Data Attribution on Diffusion Models Xiaosen Zheng Tianyu Pang Chao Du Jing Jiang Min Lin TDI 34 20 1 01 Nov 2023
Natural Example-Based Explainability: a Survey Antonin Poché Lucas Hervier M. Bakkay XAI 31 12 0 05 Sep 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 32 6 0 25 Mar 2023
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs Kelvin Guu Albert Webson Ellie Pavlick Lucas Dixon Ian Tenney Tolga Bolukbasi TDI 70 33 0 14 Mar 2023
Which Experiences Are Influential for Your Agent? Policy Iteration with Turn-over Dropout Takuya Hiraoka Takashi Onishi Yoshimasa Tsuruoka OffRL 29 0 0 26 Jan 2023
Rationalizing Predictions by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 27 4 0 15 Jan 2023
Contrastive Error Attribution for Finetuned Language Models Faisal Ladhak Esin Durmus Tatsunori Hashimoto HILM 32 9 0 21 Dec 2022
Data-Efficient Finetuning Using Cross-Task Nearest Neighbors Hamish Ivison Noah A. Smith Hannaneh Hajishirzi Pradeep Dasigi 35 20 0 01 Dec 2022
Explainability Via Causal Self-Talk Nicholas A. Roy Junkyung Kim Neil C. Rabinowitz CML 26 7 0 17 Nov 2022
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction Sunnie S. Y. Kim E. A. Watkins Olga Russakovsky Ruth C. Fong Andrés Monroy-Hernández 43 108 0 02 Oct 2022
Responsibility: An Example-based Explainable AI approach via Training Process Inspection Faraz Khadivpour Arghasree Banerjee Matthew J. Guzdial XAI 19 2 0 07 Sep 2022
Leveraging Explanations in Interactive Machine Learning: An Overview Stefano Teso Öznur Alkan Wolfgang Stammer Elizabeth M. Daly XAI FAtt LRM 26 62 0 29 Jul 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 21 36 0 08 Jun 2022
Use-Case-Grounded Simulations for Explanation Evaluation Valerie Chen Nari Johnson Nicholay Topin Gregory Plumb Ameet Talwalkar FAtt ELM 22 24 0 05 Jun 2022
ORCA: Interpreting Prompted Language Models via Locating Supporting Data Evidence in the Ocean of Pretraining Data Xiaochuang Han Yulia Tsvetkov 24 28 0 25 May 2022
TracInAD: Measuring Influence for Anomaly Detection Hugo Thimonier Fabrice Popineau Arpad Rimmel Bich-Liên Doan Fabrice Daniel TDI 19 6 0 03 May 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 27 22 0 30 Apr 2022
Attribute Prototype Network for Any-Shot Learning Wenjia Xu Yongqin Xian Jiuniu Wang Bernt Schiele Zeynep Akata VLM 34 37 0 04 Apr 2022
Label-Free Explainability for Unsupervised Models Jonathan Crabbé M. Schaar FAtt MILM 24 22 0 03 Mar 2022
PUMA: Performance Unchanged Model Augmentation for Training Data Removal Ga Wu Masoud Hashemi C. Srinivasa MU 17 69 0 02 Mar 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 42 26 0 25 Feb 2022
First is Better Than Last for Language Data Influence Chih-Kuan Yeh Ankur Taly Mukund Sundararajan Frederick Liu Pradeep Ravikumar TDI 34 20 0 24 Feb 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc A. Madry TDI 47 131 0 01 Feb 2022
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation Zayd Hammoudeh Daniel Lowd TDI 24 28 0 25 Jan 2022
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies Vivian Lai Chacha Chen Q. V. Liao Alison Smith-Renner Chenhao Tan 33 186 0 21 Dec 2021
GPEX, A Framework For Interpreting Artificial Neural Networks Amir Akbarnejad G. Bigras Nilanjan Ray 47 4 0 18 Dec 2021
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 66 114 0 06 Dec 2021
Scaling Up Influence Functions Andrea Schioppa Polina Zablotskaia David Vilar Artem Sokolov TDI 33 91 0 06 Dec 2021
Revisiting Methods for Finding Influential Examples Karthikeyan K Anders Søgaard TDI 16 30 0 08 Nov 2021
Explaining Latent Representations with a Corpus of Examples Jonathan Crabbé Zhaozhi Qian F. Imrie M. Schaar FAtt 18 37 0 28 Oct 2021
Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates Xiaochuang Han Yulia Tsvetkov TDI 31 30 0 07 Oct 2021
Longitudinal Distance: Towards Accountable Instance Attribution Rosina O. Weber Prateek Goel S. Amiri G. Simpson 16 0 0 23 Aug 2021
Influence-guided Data Augmentation for Neural Tensor Completion Sejoon Oh Sungchul Kim Ryan A. Rossi Srijan Kumar 28 10 0 23 Aug 2021
Combining Feature and Instance Attribution to Detect Artifacts Pouya Pezeshkpour Sarthak Jain Sameer Singh Byron C. Wallace TDI 18 43 0 01 Jul 2021
On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation Wei Zhang Ziming Huang Yada Zhu Guangnan Ye Xiaodong Cui Fan Zhang 31 17 0 09 Jun 2021
Explaining the Road Not Taken Hua Shen Ting-Hao 'Kenneth' Huang FAtt XAI 27 9 0 27 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 32 29 0 10 Mar 2021
Input Similarity from the Neural Network Perspective Guillaume Charpiat N. Girard Loris Felardos Y. Tarabalka 32 67 0 10 Feb 2021
Mitigating belief projection in explainable artificial intelligence via Bayesian Teaching Scott Cheng-Hsin Yang Wai Keen Vong Ravi B. Sojitra Tomas Folke Patrick Shafto 18 42 0 07 Feb 2021
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 83 262 0 03 Dec 2020