Coreset Selection via LLM-based Concept Bottlenecks

Coreset Selection via LLM-based Concept Bottlenecks

23 February 2025

Subhadra Gopalakrishnan

Papers citing "Coreset Selection via LLM-based Concept Bottlenecks"

19 / 19 papers shown

Title
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE) Usha Bhalla Alexander X. Oesterling Suraj Srinivas Flavio du Pin Calmon Himabindu Lakkaraju 105 40 0 16 Feb 2024
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning A. Maharana Prateek Yadav Mohit Bansal 83 32 0 11 Oct 2023
GPT-4 Technical Report OpenAI OpenAI OpenAI Josh Achiam Steven Adler Sandhini Agarwal Lama Ahmad ... Shengjia Zhao Tianhao Zheng Juntang Zhuang William Zhuk Barret Zoph LLMAG MLLM 1.4K 14,359 0 15 Mar 2023
Beyond neural scaling laws: beating power law scaling via data pruning Ben Sorscher Robert Geirhos Shashank Shekhar Surya Ganguli Ari S. Morcos 95 441 0 29 Jun 2022
Do Vision-Language Pretrained Models Learn Composable Primitive Concepts? Tian Yun Usha Bhalla Ellie Pavlick Chen Sun ReLM CoGe VLM LRM 62 25 0 31 Mar 2022
Natural Language Descriptions of Deep Visual Features Evan Hernandez Sarah Schwettmann David Bau Teona Bagashvili Antonio Torralba Jacob Andreas MILM 299 123 0 26 Jan 2022
Deep Learning on a Data Diet: Finding Important Examples Early in Training Mansheej Paul Surya Ganguli Gintare Karolina Dziugaite 114 457 0 15 Jul 2021
Large-Scale Zero-Shot Image Classification from Rich and Diverse Textual Descriptions Sebastian Bujwid Josephine Sullivan VLM 101 28 0 17 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 927 29,436 0 26 Feb 2021
Concept Bottleneck Models Pang Wei Koh Thao Nguyen Y. S. Tang Stephen Mussmann Emma Pierson Been Kim Percy Liang 96 823 0 09 Jul 2020
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 605 4,822 0 23 Jan 2020
A Constructive Prediction of the Generalization Error Across Scales Jonathan S. Rosenfeld Amir Rosenfeld Yonatan Belinkov Nir Shavit 101 211 0 27 Sep 2019
Coresets for Clustering with Fairness Constraints Lingxiao Huang S. Jiang Nisheeth K. Vishnoi 77 102 0 20 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 139 18,134 0 28 May 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 115 734 0 12 Dec 2018
Few-Shot Learning with Graph Neural Networks Victor Garcia Satorras Joan Bruna GNN 167 1,239 0 10 Nov 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 210 2,894 0 14 Mar 2017
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 370 7,323 0 13 Jun 2016
A Unified Framework for Approximating and Clustering Data Dan Feldman M. Langberg 147 457 0 07 Jun 2011