Feiyang Kang

According to our database, Feiyang Kang authored at least 21 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

RepMSNet: multi-scale convolutional neural network combined with structural re-parameterization for the classification of agricultural pests.

Junyan Wang, Haoran Yu, Feiyang Kang

Signal Image Video Process., April, 2026

Characterizing Model-Native Skills.

Feiyang Kang, Mahavir Dabas, Myeongseob Ko, Ruoxi Jia

CoRR, April, 2026

MixAtlas: Uncertainty-aware Data Mixture Optimization for Multimodal LLM Midtraining.

Bingbing Wen, Sirajul Salekin, Feiyang Kang, Bill Howe, Lucy Lu Wang, Javier Movellan, Manjot Bilkhu

CoRR, April, 2026

2025

Quagmires in SFT-RL Post-Training: When High SFT Scores Mislead and What to Use Instead.

Feiyang Kang, Michael Kuchnik, Karthik Padthe, Marin Vlastelica, Ruoxi Jia, Carole-Jean Wu, Newsha Ardalani

CoRR, October, 2025

AdaDeDup: Adaptive Hybrid Data Pruning for Efficient Large-Scale Object Detection Training.

Feiyang Kang, Nadine Chang, Maying Shen, Marc T. Law, Rafid Mahmood, Ruoxi Jia, José M. Álvarez

CoRR, July, 2025

Data Acquisition: A New Frontier in Data-centric AI.

Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou

J. Data-centric Mach. Learn. Res., 2025

A Sustainable AI Economy Needs Data Deals That Work for Generators.

Ruoxi Jia, Luis Oala, Wenjie Xiong, Suqin Ge, Jiachen (Tianhao) Wang, Feiyang Kang, Dawn Song

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls.

Feiyang Kang, Newsha Ardalani, Michael Kuchnik, Youssef Emad, Mostafa Elhoushi, Shubhabrata Sengupta, Shang-wen Li, Ramya Raghavendra, Ruoxi Jia, Carole-Jean Wu

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

2024

Data-Centric Defense: Shaping Loss Landscape with Augmentations to Counter Model Inversion.

Si Chen, Feiyang Kang, Nikhil Abhyankar, Ming Jin, Ruoxi Jia

Trans. Mach. Learn. Res., 2024

AutoScale: Automatic Prediction of Compute-optimal Data Composition for Training LLMs.

Feiyang Kang, Yifan Sun, Bingbing Wen, Si Chen, Dawn Song, Rafid Mahmood, Ruoxi Jia

CoRR, 2024

FASTTRACK: Fast and Accurate Fact Tracing for LLMs.

Si Chen, Feiyang Kang, Ning Yu, Ruoxi Jia

CoRR, 2024

Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs.

Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FASTTRACK: Reliable Fact Tracing via Clustering and LLM-Powered Evidence Validation.

Si Chen, Feiyang Kang, Ning Yu, Ruoxi Jia

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes.

Myeongseob Ko, Feiyang Kang, Weiyan Shi, Ming Jin, Zhou Yu, Ruoxi Jia

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

LAVA: Data Valuation without Pre-Specified Learning Algorithms.

Hoang Anh Just, Feiyang Kang, Jiachen T. Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia

CoRR, 2023

Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources.

Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Robustness Certification Against Universal Perturbations.

Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia

Proceedings of the Eleventh International Conference on Learning Representations, 2023

LAVA: Data Valuation without Pre-Specified Learning Algorithms.

Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia

Proceedings of the Eleventh International Conference on Learning Representations, 2023

RepCFT: A Fusion Model of Reparameterized Convolutional Neural Network and Visual Transformer for Wood Species Recognition.

Junyan Wang, Ziyan Lian, Feiyang Kang, Jinkai Chen

Proceedings of the 4th International Conference on Artificial Intelligence and Computer Engineering, 2023

2021

Visual Navigation with a 2-pixel Camera - Possibilities and Limitations.

John Baillieul, Feiyang Kang

CoRR, 2021

2018

Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators.

Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang

Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018