Junhong Lin - RankMe

72 papers A* 7A 1B 1C 1Journal 58Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AutoDrive-P CoRR Yuqi Ye, Zijian Zhang, Junhong Lin, Shangkun Sun, Changhao Peng, Wei Gao
2026	J	`jnl`	ConstellationNet: Reinventing Clustering Through GNNs. Mach. Learn. Aidan Gao, Junhong Lin
2026	J	`jnl`	HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs. CoRR Xinyue Zeng, Junhong Lin, Yujun Yan, Feng Guo, Liang Shi, Jun Wu, Dawei Zhou
2026	J	`jnl`	How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge. CoRR Junhong Lin, Bing Zhang, Song Wang, Ziyan Liu, Dan Gutfreund, Julian Shun, Yada Zhu
2026	J	`jnl`	Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces. CoRR Mike A. Merrill, Alexander Glenn Shaw, Nicholas Carlini, Boxuan Li, Harsh Raj, Ivan Bercovich, Lin Shi, Jeong Yeon Shin, Thomas Walshe, Estefany Kelly Buchanan, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, Marianna Nezhurina, Jenia Jitsev, Di Lu, Orfeas Menis-Mastromichalakis, Zhiwei Xu, Zizhao Chen, Yue Liu, Robert Zhang, Leon Liangyu Chen, Anurag Kashyap, Jan-Lucas Uslu, Jeffrey Li, Jianbo Wu, Minghao Yan, Song Bian, Vedang Sharma, Ke Sun, Steven Dillmann, Akshay Anand, Andrew Lanpouthakoun, Bardia Koopah, Changran Hu, Etash Kumar Guha, Gabriel H. S. Dreiman, Jiacheng Zhu, Karl Krauth, Li Zhong, Niklas Muennighoff, Robert Amanfu, Shangyin Tan, Shreyas Pimpalgaonkar, Tushar Aggarwal, Xiangning Lin, Xin Lan, Xuandong Zhao, Yiqing Liang, Yuanli Wang, Zilong Wang, Changzhi Zhou, David Heineman, Hange Liu, Harsh Trivedi, John Yang, Junhong Lin, Manish Shetty, Michael Yang, Nabil Omi, Negin Raoof, Shanda Li, Terry Yue Zhuo, Wuwei Lin, Yiwei Dai, Yuxin Wang, Wenhao Chai, Shang Zhou, Dariush Wahdany, Ziyu She, Jiaming Hu, Zhikang Dong, Yuxuan Zhu, Sasha Cui, Ahson Saiyed, Arinbjörn Kolbeinsson, Jesse Hu, Christopher Michael Rytting, Ryan Marten, Yixin Wang, Alex Dimakis, Andy Konwinski, Ludwig Schmidt
2025	J	`jnl`	ConstellationNet: Reinventing Spatial Clustering through GNNs. CoRR Aidan Gao, Junhong Lin
2025	J	`jnl`	HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations. CoRR Shuaicheng Zhang, Haohui Wang, Junhong Lin, Xiaojie Guo, Yada Zhu, Si Zhang, Dongqi Fu, Dawei Zhou
2025	J	`jnl`	High probability bounds on AdaGrad for constrained weakly convex optimization. J. Complex. Yusu Hong, Junhong Lin
2025	J	`jnl`	LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. CoRR Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou
2025	J	`jnl`	Layered Division and Global Allocation for Community Detection in Multilayer Network. CoRR Fanghao Hu, Junhong Lin, Zhi Cai, Bang Wang
2025	A*	`conf`	LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. ICML Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou
2025	J	`jnl`	Low-Light Aerial Imaging With Color and Monochrome Cameras. IEEE Trans. Geosci. Remote. Sens. Pengwu Yuan, Liqun Lin, Junhong Lin, Yipeng Liao, Tiesong Zhao
2025	J	`jnl`	Plan and Budget: Effective and Efficient Test-Time Scaling on Large Language Model Reasoning. CoRR Junhong Lin, Xinyue Zeng, Jie Zhu, Song Wang, Julian Shun, Jun Wu, Dawei Zhou
2025	A*	`conf`	Reasoning of Large Language Models over Knowledge Graphs with Super-Relations. ICLR Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu
2025	J	`jnl`	Reasoning of Large Language Models over Knowledge Graphs with Super-Relations. CoRR Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu
2025	J	`jnl`	Temporal Reasoning with Large Language Models Augmented by Evolving Knowledge Graphs. CoRR Junhong Lin, Song Wang, Xiaojie Guo, Julian Shun, Yada Zhu
2025	J	`jnl`	VGD: Visual Geometry Gaussian Splatting for Feed-Forward Surround-view Driving Reconstruction. CoRR Junhong Lin, Kangli Wang, Shunzhou Wang, Songlin Fan, Ge Li, Wei Gao
2025	—	`conf`	When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark. KDD (2) Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Yada Zhu, Julian Shun
2024	J	`jnl`	Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images. CoRR Shufan Pei, Junhong Lin, Wenxi Liu, Tiesong Zhao, Chia-Wen Lin
2024	J	`jnl`	Convergence of projected subgradient method with sparse or low-rank constraints. Adv. Comput. Math. Hang Xu, Song Li, Junhong Lin
2024	—	`conf`	FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection. ICAIF Junhong Lin, Xiaojie Guo, Yada Zhu, Samuel Mitchell, Erik Altman, Julian Shun
2024	J	`jnl`	Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review. CoRR Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, Junhong Lin
2024	J	`jnl`	Nonconvex Deterministic Matrix Completion by Projected Gradient Descent Methods. CoRR Hang Xu, Song Li, Junhong Lin
2024	A*	`conf`	On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions. NeurIPS Yusu Hong, Junhong Lin
2024	J	`jnl`	On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions. CoRR Yusu Hong, Junhong Lin
2024	J	`jnl`	PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network. CoRR Tan Sun, Junhong Lin
2024	A	`conf`	Revisiting Convergence of AdaGrad with Relaxed Assumptions. UAI Yusu Hong, Junhong Lin
2024	J	`jnl`	Revisiting Convergence of AdaGrad with Relaxed Assumptions. CoRR Yusu Hong, Junhong Lin
2024	J	`jnl`	Robust Domain Generalization for Multi-modal Object Recognition. CoRR Yuxin Qiao, Keqin Li, Junhong Lin, Rong Wei, Chufeng Jiang, Yang Luo, Haoyu Yang
2024	B	`conf`	UnifiedGT: Towards a Universal Framework of Transformers in Large-Scale Graph Learning. IEEE Big Data Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun
2024	J	`jnl`	When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods. CoRR Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun
2023	J	`jnl`	High Probability Convergence of Adam Under Unbounded Gradients and Affine Variance Noise. CoRR Yusu Hong, Junhong Lin
2023	A*	`conf`	LDRM: Degradation Rectify Model for Low-light Imaging via Color-Monochrome Cameras. ACM Multimedia Junhong Lin, Shufan Pei, Bing Chen, Nanfeng Jiang, Wei Gao, Tiesong Zhao
2023	J	`jnl`	LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal. IEEE Trans. Circuits Syst. Video Technol. Junhong Lin, Nanfeng Jiang, ZhenTao Zhang, Weiling Chen, Tiesong Zhao
2023	J	`jnl`	Lightweight Semi-supervised Network for Single Image Rain Removal. Pattern Recognit. Nanfeng Jiang, Jiawei Luo, Junhong Lin, Weiling Chen, Tiesong Zhao
2023	J	`jnl`	Low-Light Image Enhancement via Stage-Transformer-Guided Network. IEEE Trans. Circuits Syst. Video Technol. Nanfeng Jiang, Junhong Lin, Ting Zhang, Haifeng Zheng, Tiesong Zhao
2023	—	`conf`	Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. Bildverarbeitung für die Medizin Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy, Yunchan Hwang, Stefan B. Ploner, Junhong Lin, Jessica Girgis, Kenneth Lam, Siyu Chen, Nadia K. Waheed, Andreas K. Maier, James G. Fujimoto
2023	J	`jnl`	Unsupervised detection of small hyperreflective features in ultrahigh resolution optical coherence tomography. CoRR Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy, Yunchan Hwang, Stefan B. Ploner, Junhong Lin, Jessica Girgis, Kenneth Lam, Siyu Chen, Nadia K. Waheed, Andreas K. Maier, James G. Fujimoto
2022	C	`conf`	DesnowFormer: an effective transformer-based image desnowing network. VCIP Ting Zhang, Nanfeng Jiang, Junhong Lin, Jielian Lin, Tiesong Zhao
2022	J	`jnl`	LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal. CoRR Junhong Lin, Nanfeng Jiang, ZhenTao Zhang, Weiling Chen, Tiesong Zhao
2020	J	`jnl`	Beetle Swarm Optimization Algorithm-Based Load Control with Electricity Storage. J. Control. Sci. Eng. Hengjing He, Shangli Zhou, Leping Zhang, Junhong Lin, Weile Chen, Di Wu
2020	J	`jnl`	Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. J. Mach. Learn. Res. Junhong Lin, Volkan Cevher
2020	J	`jnl`	Iterative hard thresholding for compressed data separation. J. Complex. Song Li, Junhong Lin, Dekai Liu, Wenchang Sun
2020	J	`jnl`	Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms. J. Mach. Learn. Res. Junhong Lin, Volkan Cevher
2019	J	`jnl`	A Learning-Based Framework for Quantized Compressed Sensing. IEEE Signal Process. Lett. Rabeeh Karimi Mahabadi, Junhong Lin, Volkan Cevher
2018	J	`jnl`	Generalization properties of doubly stochastic learning algorithms. J. Complex. Junhong Lin, Lorenzo Rosasco
2018	J	`jnl`	Indoor Localization Based on Weighted Surfacing from Crowdsourced Samples. Sensors Junhong Lin, Bang Wang, Guang Yang, Mu Zhou
2018	J	`jnl`	Kernel Conjugate Gradient Methods with Random Projections. CoRR Junhong Lin, Volkan Cevher
2018	J	`jnl`	Modified Fejér sequences and applications. Comput. Optim. Appl. Junhong Lin, Lorenzo Rosasco, Silvia Villa, Ding-Xuan Zhou
2018	J	`jnl`	Online Learning Algorithms Can Converge Comparably Fast as Batch Learning. IEEE Trans. Neural Networks Learn. Syst. Junhong Lin, Ding-Xuan Zhou
2018	J	`jnl`	Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms. CoRR Junhong Lin, Volkan Cevher
2018	A*	`conf`	Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods. ICML Junhong Lin, Volkan Cevher
2018	J	`jnl`	Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces. CoRR Junhong Lin, Volkan Cevher
2018	A*	`conf`	Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. ICML Junhong Lin, Volkan Cevher
2018	J	`jnl`	Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. CoRR Junhong Lin, Volkan Cevher
2017	J	`jnl`	Generalization Properties of Doubly Online Learning Algorithms. CoRR Junhong Lin, Lorenzo Rosasco
2017	J	`jnl`	Online pairwise learning algorithms with convex loss functions. Inf. Sci. Junhong Lin, Yunwen Lei, Bo Zhang, Ding-Xuan Zhou
2017	J	`jnl`	Optimal Rates for Learning with Nyström Stochastic Gradient Methods. CoRR Junhong Lin, Lorenzo Rosasco
2017	J	`jnl`	Optimal Rates for Multi-pass Stochastic Gradient Methods. J. Mach. Learn. Res. Junhong Lin, Lorenzo Rosasco
2016	A*	`conf`	Generalization Properties and Implicit Regularization for Multiple Passes SGM. ICML Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco
2016	J	`jnl`	Generalization Properties and Implicit Regularization for Multiple Passes SGM. CoRR Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco
2016	J	`jnl`	Iterative Regularization for Learning with Convex Loss Functions. J. Mach. Learn. Res. Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou
2016	—	`conf`	Optimal Learning for Multi-pass Stochastic Gradient Methods. NIPS Junhong Lin, Lorenzo Rosasco
2016	J	`jnl`	Optimal Learning for Multi-pass Stochastic Gradient Methods. CoRR Junhong Lin, Lorenzo Rosasco
2016	J	`jnl`	Restricted $q$-Isometry Properties Adapted to Frames for Nonconvex $l_q$-Analysis. CoRR Junhong Lin, Song Li
2016	J	`jnl`	Restricted q-Isometry Properties Adapted to Frames for Nonconvex l IEEE Trans. Inf. Theory Junhong Lin, Song Li
2015	J	`jnl`	Learning theory of randomized Kaczmarz algorithm. J. Mach. Learn. Res. Junhong Lin, Ding-Xuan Zhou
2013	J	`jnl`	Compressed Data Separation With Redundant Dictionaries. IEEE Trans. Inf. Theory Junhong Lin, Song Li, Yi Shen
2013	J	`jnl`	New Bounds for Restricted Isometry Constants With Coherent Tight Frames. IEEE Trans. Signal Process. Junhong Lin, Song Li, Yi Shen
2013	J	`jnl`	Nonuniform support recovery from noisy random measurements by Orthogonal Matching Pursuit. J. Approx. Theory Junhong Lin, Song Li
2013	J	`jnl`	Sparse Recovery with Coherent Tight Frame via Analysis Dantzig Selector and Analysis LASSO CoRR Junhong Lin, Song Li
2011	J	`jnl`	Compressed Sensing with coherent tight frames via $l_q$-minimization for $0<q\leq1$ CoRR Song Li, Junhong Lin