Ruqi Zhang - RankMe

96 papers A* 22A 7C 1Journal 62Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion. CoRR Jiaru Zhang, Manav Gagvani, Can Cui, Juntong Peng, Ruqi Zhang, Ziran Wang
2026	A*	`conf`	Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange. AAAI Haoyang Zheng, Hengrong Du, Ruqi Zhang, Guang Lin
2026	J	`jnl`	Learning From Developers: Towards Reliable Patch Validation at Scale for Linux. CoRR Chih-En Lin, Attreyee Mukherjee, Ajay Rawat, Ruqi Zhang, Pedro Fonseca
2026	J	`jnl`	Learning Self-Correction in Vision-Language Models via Rollout Augmentation. CoRR Yi Ding, Ziliang Qiu, Bolian Li, Ruqi Zhang
2026	J	`jnl`	Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World. CoRR Joonkyung Kim, Wenxi Chen, Davood Soleymanzadeh, Yi Ding, Xiangbo Gao, Zhengzhong Tu, Ruqi Zhang, Fan Fei, Sushant Veer, Yiwei Lyu, Minghui Zheng, Yan Gu
2026	J	`jnl`	SARL: Label-Free Reinforcement Learning by Rewarding Reasoning Topology. CoRR Yifan Wang, Bolian Li, David Cho, Ruqi Zhang, Fanping Sui, Ananth Grama
2026	J	`jnl`	Who Tests the Testers? Systematic Enumeration and Coverage Audit of LLM Agent Tool Call Safety. CoRR Xuan Chen, Lu Yan, Ruqi Zhang, Xiangyu Zhang
2026	J	`jnl`	Why Any-Order Autoregressive Models Need Two-Stream Attention: A Structural-Semantic Tradeoff. CoRR Patrick Pynadath, Ruqi Zhang
2025	A*	`conf`	Adaptive Draft-Verification for Efficient Large Language Model Decoding. AAAI Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu
2025	J	`jnl`	Bayesian Computation in Deep Learning. CoRR Wenlong Chen, Bolian Li, Ruqi Zhang, Yingzhen Li
2025	J	`jnl`	CANDI: Hybrid Discrete-Continuous Diffusion Models. CoRR Patrick Pynadath, Jiaxin Shi, Ruqi Zhang
2025	—	`conf`	CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought. ACL (Findings) Boxuan Zhang, Ruqi Zhang
2025	J	`jnl`	CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought. CoRR Boxuan Zhang, Ruqi Zhang
2025	A*	`conf`	Controlled LLM Decoding via Discrete Auto-regressive Biasing. ICLR Patrick Pynadath, Ruqi Zhang
2025	J	`jnl`	Controlled LLM Decoding via Discrete Auto-regressive Biasing. CoRR Patrick Pynadath, Ruqi Zhang
2025	J	`jnl`	DRIFT: Learning from Abundant User Dissatisfaction in Real-World Preference Learning. CoRR Yifan Wang, Bolian Li, Junlin Wu, Zhaoxuan Tan, Zheli Liu, Ruqi Zhang, Ananth Grama, Qingkai Zeng
2025	A	`conf`	Dynamic Obstacle Avoidance through Uncertainty-Based Adaptive Planning with Diffusion. IROS Vineet Punyamoorty, Pascal Jutras-Dubé, Ruqi Zhang, Vaneet Aggarwal, Damon Conover, Aniket Bera
2025	A*	`conf`	ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time. ICLR Yi Ding, Bolian Li, Ruqi Zhang
2025	J	`jnl`	Energy-Based Reward Models for Robust Language Model Alignment. CoRR Anamika Lochab, Ruqi Zhang
2025	J	`jnl`	Entropy-Guided Sampling of Flat Modes in Discrete Spaces. CoRR Pinaki Mohanty, Riddhiman Bhattacharya, Ruqi Zhang
2025	J	`jnl`	Exploring Non-Convex Discrete Energy Landscapes: A Langevin-Like Sampler with Replica Exchange. CoRR Haoyang Zheng, Ruqi Zhang, Guang Lin
2025	J	`jnl`	Gradient GA: Gradient Genetic Algorithm For Drug Molecular Design. Trans. Mach. Learn. Res. Debadyuti Mukherjee, Chris Zhuang, Yingzhou Lu, Tianfan Fu, Ruqi Zhang
2025	J	`jnl`	Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design. CoRR Chris Zhuang, Debadyuti Mukherjee, Yingzhou Lu, Tianfan Fu, Ruqi Zhang
2025	J	`jnl`	Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding. CoRR Jiaru Zhang, Juanwu Lu, Ziran Wang, Ruqi Zhang
2025	J	`jnl`	Making Reliable and Flexible Decisions in Long-tailed Classification. CoRR Bolian Li, Ruqi Zhang
2025	J	`jnl`	Making Reliable and Flexible Decisions in Long-tailed Classification. Trans. Mach. Learn. Res. Bolian Li, Ruqi Zhang
2025	J	`jnl`	More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment. CoRR Yifan Wang, Runjin Chen, Bolian Li, David Cho, Yihe Deng, Ruqi Zhang, Tianlong Chen, Zhangyang Wang, Ananth Grama, Junyuan Hong
2025	A	`conf`	On Learning Closed-Loop Probabilistic Multi-Agent Simulator. IROS Juanwu Lu, Rohit Gupta, Ahmadreza Moradipari, Kyungtae Han, Ruqi Zhang, Ziran Wang
2025	J	`jnl`	On Learning Closed-Loop Probabilistic Multi-Agent Simulator. CoRR Juanwu Lu, Rohit Gupta, Ahmadreza Moradipari, Kyungtae Han, Ruqi Zhang, Ziran Wang
2025	J	`jnl`	One-Step Diffusion Samplers via Self-Distillation and Deterministic Flow. CoRR Pascal Jutras-Dube, Jiaru Zhang, Ziran Wang, Ruqi Zhang
2025	A	`conf`	Optimal Stochastic Trace Estimation in Generative Modeling. AISTATS Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang
2025	J	`jnl`	Optimal Stochastic Trace Estimation in Generative Modeling. CoRR Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang
2025	J	`jnl`	Reheated Gradient-based Discrete Sampling for Combinatorial Optimization. CoRR Muheng Li, Ruqi Zhang
2025	J	`jnl`	Reheated Gradient-based Discrete Sampling for Combinatorial Optimization. Trans. Mach. Learn. Res. Muheng Li, Ruqi Zhang
2025	A*	`conf`	Reward-Shifted Speculative Sampling Is An Efficient Test-Time Weak-to-Strong Aligner. EMNLP Bolian Li, Yanran Wu, Xinyu Luo, Ruqi Zhang
2025	J	`jnl`	Reward-Shifted Speculative Sampling Is An Efficient Test-Time Weak-to-Strong Aligner. CoRR Bolian Li, Yanran Wu, Xinyu Luo, Ruqi Zhang
2025	A*	`conf`	Scalable and Efficient Probabilistic Inference for Bayesian Deep Learning and Generative Modeling. AAAI Ruqi Zhang
2025	J	`jnl`	Sherlock: Self-Correcting Reasoning in Vision-Language Models. CoRR Yi Ding, Ruqi Zhang
2025	J	`jnl`	Single-Step Consistent Diffusion Samplers. CoRR Pascal Jutras-Dubé, Patrick Pynadath, Ruqi Zhang
2025	J	`jnl`	Stacey: Promoting Stochastic Steepest Descent via Accelerated ℓ CoRR Xinyu Luo, Cedar Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang, Brian Bullins
2025	A*	`conf`	Stacey: Promoting Stochastic Steepest Descent via Accelerated ℓp-Smooth Nonconvex Optimization. ICML Xinyu Luo, Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang, Brian Bullins
2025	J	`jnl`	TraceAwareness and dual-strategy fuzz testing: Enhancing path coverage and crash localization with stochastic science and large language models. Comput. Electr. Eng. Xiaoquan Chen, Jian Liu, Yingkai Zhang, Qinsong Hu, Yupeng Han, Ruqi Zhang, Jingqi Ran, Lei Yan, Baiqi Huang, Shengtin Ma
2025	J	`jnl`	VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models. CoRR Qilin Liao, Anamika Lochab, Ruqi Zhang
2025	J	`jnl`	VERA: Variational Inference Framework for Jailbreaking Large Language Models. CoRR Anamika Lochab, Lu Yan, Patrick Pynadath, Xiangyu Zhang, Ruqi Zhang
2025	J	`jnl`	ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving. CoRR Can Cui, Yupeng Zhou, Juntong Peng, Sung-Yeon Park, Zichong Yang, Prashanth Sankaranarayanan, Jiaru Zhang, Ruqi Zhang, Ziran Wang
2024	J	`jnl`	Adaptive Draft-Verification for Efficient Large Language Model Decoding. CoRR Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu
2024	A	`conf`	Adaptive Planning with Generative Models under Uncertainty. IROS Pascal Jutras-Dubé, Ruqi Zhang, Aniket Bera
2024	J	`jnl`	Adaptive Planning with Generative Models under Uncertainty. CoRR Pascal Jutras-Dubé, Ruqi Zhang, Aniket Bera
2024	—	`conf`	Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction. CPAL Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick
2024	J	`jnl`	Cascade Reward Sampling for Efficient Decoding-Time Alignment. CoRR Bolian Li, Yifan Wang, Ananth Grama, Ruqi Zhang
2024	J	`jnl`	Dynamic Obstacle Avoidance through Uncertainty-Based Adaptive Planning with Diffusion. CoRR Vineet Punyamoorty, Pascal Jutras-Dubé, Ruqi Zhang, Vaneet Aggarwal, Damon Conover, Aniket Bera
2024	J	`jnl`	ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time. CoRR Yi Ding, Bolian Li, Ruqi Zhang
2024	J	`jnl`	Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. CoRR Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick
2024	J	`jnl`	Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. Trans. Mach. Learn. Res. Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick
2024	J	`jnl`	Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. Trans. Mach. Learn. Res. Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
2024	A*	`conf`	Entropy-MCMC: Sampling from Flat Basins with Ease. ICLR Bolian Li, Ruqi Zhang
2024	A*	`conf`	Gradient-based Discrete Sampling with Automatic Cyclical Scheduling. NeurIPS Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang
2024	J	`jnl`	Gradient-based Discrete Sampling with Automatic Cyclical Scheduling. CoRR Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Training Bayesian Neural Networks with Sparse Subspace Variational Inference. ICLR Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang
2024	J	`jnl`	Training Bayesian Neural Networks with Sparse Subspace Variational Inference. CoRR Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang
2023	C	`conf`	Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. AIES Tunazzina Islam, Ruqi Zhang, Dan Goldwasser
2023	J	`jnl`	Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. CoRR Tunazzina Islam, Ruqi Zhang, Dan Goldwasser
2023	J	`jnl`	Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction. CoRR Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick
2023	A*	`conf`	Calibrating the Rigged Lottery: Making All Tickets Reliable. ICLR Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick
2023	J	`jnl`	Calibrating the Rigged Lottery: Making All Tickets Reliable. CoRR Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick
2023	A*	`conf`	DISCS: A Benchmark for Discrete Sampling. NeurIPS Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai
2023	A*	`conf`	DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference. ICML Wanrong Zhang, Ruqi Zhang
2023	J	`jnl`	DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference. CoRR Wanrong Zhang, Ruqi Zhang
2023	A	`conf`	Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. AISTATS Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang
2023	J	`jnl`	Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. CoRR Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang
2023	J	`jnl`	Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. CoRR Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
2023	J	`jnl`	Entropy-MCMC: Sampling from Flat Basins with Ease. CoRR Bolian Li, Ruqi Zhang
2023	J	`jnl`	Long-tailed Classification from a Bayesian-decision-theory Perspective. CoRR Bolian Li, Ruqi Zhang
2023	A*	`conf`	Rethinking Data Distillation: Do Not Overlook Calibration. ICCV Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang
2023	J	`jnl`	Rethinking Data Distillation: Do Not Overlook Calibration. CoRR Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang, Ruqi Zhang, Yiqun Xie, Dongkuan Xu
2022	A*	`conf`	A Langevin-like Sampler for Discrete Distributions. ICML Ruqi Zhang, Xingchao Liu, Qiang Liu
2022	J	`jnl`	A Langevin-like Sampler for Discrete Distributions. CoRR Ruqi Zhang, Xingchao Liu, Qiang Liu
2022	A*	`conf`	Low-Precision Stochastic Gradient Langevin Dynamics. ICML Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa
2022	J	`jnl`	Low-Precision Stochastic Gradient Langevin Dynamics. CoRR Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa
2022	A*	`conf`	Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. NeurIPS Ruqi Zhang, Qiang Liu, Xin T. Tong
2022	J	`jnl`	Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. CoRR Ruqi Zhang, Qiang Liu, Xin T. Tong
2021	A	`conf`	Meta-Learning Divergences for Variational Inference. AISTATS Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
2020	A	`conf`	AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. AISTATS Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	J	`jnl`	AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. CoRR Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	A*	`conf`	Asymptotically Optimal Exact Minibatch Metropolis-Hastings. NeurIPS Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	J	`jnl`	Asymptotically Optimal Exact Minibatch Metropolis-Hastings. CoRR Ruqi Zhang, A. Feder Cooper, Christopher De Sa
2020	A*	`conf`	Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. ICLR Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson
2020	J	`jnl`	Meta-Learning for Variational Inference. CoRR Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
2019	J	`jnl`	Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. CoRR Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson
2019	A*	`conf`	Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees. NeurIPS Ruqi Zhang, Christopher De Sa
2019	J	`jnl`	Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees. CoRR Ruqi Zhang, Christopher De Sa
2018	—	`conf`	Acupoint Selection Rule Mining of Premature Ovarian Failure Treatment with Acupuncture and Moxibustion Based on the Data Analysis of Clinical Literature. BIBM Xiaochun Han, Yanni Fan, Haijun Zhao, Shijun Wang, Sisheng Tian, Hongyuan Zhang, Zhe Yang, Ruqi Zhang, Jing Zhang, Wei Shi
2016	A*	`conf`	Large Scale Sparse Clustering. IJCAI Ruqi Zhang, Zhiwu Lu
2015	—	`conf`	Denoising Cluster Analysis. ICONIP (3) Ruqi Zhang, Zhirong Yang, Jukka Corander