Lily Weng - RankMe

14 papers A* 10A 1Journal 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions. CoRR Saleh Afroogh, Seyd Ishtiaque Ahmed, Petra Ahrweiler, David Alvarez-Melis, Mansur Maturidi Arief, Emilia Barakova, Falco J. Bargagli-Stoffi, Erdem Biyik, Hanjie Chen, Xiang 'Anthony' Chen, Robert Clements, Keeley Crockett, Amit Dhurandhar, Fethiye Irmak Dogan, Mollie Dollinger, Motahhare Eslami, Aldo A. Faisal, Arya Farahi, Melanie Fernandez Pradie, Saadia Gabrie, Diego Garcia-Olano, Marzyeh Ghassemi, Shaona Ghosh, Hatice Gunes, Ehsan Hajiramezanali, Stefan Haufe, Biwei Huang, Angel Hwang, Md Tauhidul Islam, Junfeng Jiao, Amir-Hossein Karimi, Saber Kazeminasab, Anastasia Kuzminykh, William G. La Cava, Brian Y. Lim, Xiaofeng Liu, Mohammad R. K. Mofrad, Alicia Parrish, María Pérez-Ortiz, Shriti Raj, Swabha Swayamdipta, Salmon Talebi, Kush R. Varshney, Mihaela Vorvoreanu, Lily Weng, Alice Xiang, Yiming Xu, Ding Zhao, Jieyu Zhao
2024	A*	`conf`	Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification. NeurIPS Yunshi Wen, Tengfei Ma, Lily Weng, Lam M. Nguyen, Anak Agung Julius
2024	A*	`conf`	Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data. NeurIPS Pei-Yau Weng, Minh Hoang, Lam M. Nguyen, My T. Thai, Lily Weng, Trong Nghia Hoang
2024	A*	`conf`	Provable and Efficient Dataset Distillation for Kernel Ridge Regression. NeurIPS Yilan Chen, Wei Huang, Lily Weng
2024	A*	`conf`	VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance. NeurIPS Divyansh Srivastava, Ge Yan, Lily Weng
2023	A*	`conf`	Analyzing Generalization of Neural Networks through Loss Path Kernels. NeurIPS Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam M. Nguyen, Lily Weng
2022	J	`jnl`	Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning. CoRR Alex Gu, Songtao Lu, Parikshit Ram, Lily Weng
2022	A*	`conf`	Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. ICML Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
2021	A*	`conf`	Fast Training of Provably Robust Neural Networks by SingleProp. AAAI Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel
2021	A	`conf`	Hidden Cost of Randomized Smoothing. AISTATS Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2021	J	`jnl`	Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. CoRR Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
2020	A*	`conf`	Neural Network Control Policy Verification With Persistent Adversarial Perturbation. ICML Yuh-Shyang Wang, Lily Weng, Luca Daniel
2019	A*	`conf`	POPQORN: Quantifying Robustness of Recurrent Neural Networks. ICML Ching-Yun Ko, Zhaoyang Lyu, Lily Weng, Luca Daniel, Ngai Wong, Dahua Lin
2019	A*	`conf`	PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach. ICML Lily Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Akhilan Boopathy, Ivan V. Oseledets, Luca Daniel