Ruqi Zhang

According to our database, Ruqi Zhang authored at least 53 papers between 2015 and 2025.

Collaborative distances:

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

2025

Reward-Shifted Speculative Sampling Is An Efficient Test-Time Weak-to-Strong Aligner.

Bolian Li, Yanran Wu, Xinyu Luo, Ruqi Zhang

CoRR, August, 2025

ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving.

Can Cui, Yupeng Zhou, Juntong Peng, Sung-Yeon Park, Zichong Yang, Prashanth Sankaranarayanan, Jiaru Zhang, Ruqi Zhang, Ziran Wang

CoRR, August, 2025

On Learning Closed-Loop Probabilistic Multi-Agent Simulator.

Juanwu Lu, Rohit Gupta, Ahmadreza Moradipari, Kyungtae Han, Ruqi Zhang, Ziran Wang

CoRR, August, 2025

VERA: Variational Inference Framework for Jailbreaking Large Language Models.

Anamika Lochab, Lu Yan, Patrick Pynadath, Xiangyu Zhang, Ruqi Zhang

CoRR, June, 2025

Stacey: Promoting Stochastic Steepest Descent via Accelerated ℓ_p-Smooth Nonconvex Optimization.

Xinyu Luo, Cedar Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang, Brian Bullins

CoRR, June, 2025

Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding.

Jiaru Zhang, Juanwu Lu, Ziran Wang, Ruqi Zhang

CoRR, May, 2025

Sherlock: Self-Correcting Reasoning in Vision-Language Models.

Yi Ding, Ruqi Zhang

CoRR, May, 2025

Entropy-Guided Sampling of Flat Modes in Discrete Spaces.

Pinaki Mohanty, Riddhiman Bhattacharya, Ruqi Zhang

CoRR, May, 2025

Energy-Based Reward Models for Robust Language Model Alignment.

Anamika Lochab, Ruqi Zhang

CoRR, April, 2025

More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment.

Yifan Wang, Runjin Chen, Bolian Li, David Cho, Yihe Deng, Ruqi Zhang, Tianlong Chen, Zhangyang Wang, Ananth Grama, Junyuan Hong

CoRR, April, 2025

Bayesian Computation in Deep Learning.

Wenlong Chen, Bolian Li, Ruqi Zhang, Yingzhen Li

CoRR, February, 2025

Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design.

Chris Zhuang, Debadyuti Mukherjee, Yingzhou Lu, Tianfan Fu, Ruqi Zhang

CoRR, February, 2025

Single-Step Consistent Diffusion Samplers.

Pascal Jutras-Dubé, Patrick Pynadath, Ruqi Zhang

CoRR, February, 2025

Exploring Non-Convex Discrete Energy Landscapes: A Langevin-Like Sampler with Replica Exchange.

Haoyang Zheng, Ruqi Zhang, Guang Lin

CoRR, January, 2025

Reheated Gradient-based Discrete Sampling for Combinatorial Optimization.

Muheng Li, Ruqi Zhang

Trans. Mach. Learn. Res., 2025

Making Reliable and Flexible Decisions in Long-tailed Classification.

Bolian Li, Ruqi Zhang

Trans. Mach. Learn. Res., 2025

TraceAwareness and dual-strategy fuzz testing: Enhancing path coverage and crash localization with stochastic science and large language models.

Xiaoquan Chen, Jian Liu, Yingkai Zhang, Qinsong Hu, Yupeng Han, Ruqi Zhang, Jingqi Ran, Lei Yan, Baiqi Huang, Shengtin Ma

Comput. Electr. Eng., 2025

Controlled LLM Decoding via Discrete Auto-regressive Biasing.

Patrick Pynadath, Ruqi Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time.

Yi Ding, Bolian Li, Ruqi Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Optimal Stochastic Trace Estimation in Generative Modeling.

Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought.

Boxuan Zhang, Ruqi Zhang

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Scalable and Efficient Probabilistic Inference for Bayesian Deep Learning and Generative Modeling.

Ruqi Zhang

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Adaptive Draft-Verification for Efficient Large Language Model Decoding.

Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo.

Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang

Trans. Mach. Learn. Res., 2024

Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick

Trans. Mach. Learn. Res., 2024

Dynamic Obstacle Avoidance through Uncertainty-Based Adaptive Planning with Diffusion.

Vineet Punyamoorty, Pascal Jutras-Dubé, Ruqi Zhang, Vaneet Aggarwal, Damon Conover, Aniket Bera

CoRR, 2024

Cascade Reward Sampling for Efficient Decoding-Time Alignment.

Bolian Li, Yifan Wang, Ananth Grama, Ruqi Zhang

CoRR, 2024

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.

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

CoRR, 2024

Gradient-based Discrete Sampling with Automatic Cyclical Scheduling.

Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Adaptive Planning with Generative Models under Uncertainty.

Pascal Jutras-Dubé, Ruqi Zhang, Aniket Bera

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Entropy-MCMC: Sampling from Flat Basins with Ease.

Bolian Li, Ruqi Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Training Bayesian Neural Networks with Sparse Subspace Variational Inference.

Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick

Proceedings of the Conference on Parsimony and Learning, 2024

2023

Long-tailed Classification from a Bayesian-decision-theory Perspective.

Bolian Li, Ruqi Zhang

CoRR, 2023

DISCS: A Benchmark for Discrete Sampling.

Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai

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

DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference.

Wanrong Zhang, Ruqi Zhang

Proceedings of the International Conference on Machine Learning, 2023

Calibrating the Rigged Lottery: Making All Tickets Reliable.

Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Rethinking Data Distillation: Do Not Overlook Calibration.

Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation.

Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging.

Tunazzina Islam, Ruqi Zhang, Dan Goldwasser

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent.

Ruqi Zhang, Qiang Liu, Xin T. Tong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Low-Precision Stochastic Gradient Langevin Dynamics.

Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa

Proceedings of the International Conference on Machine Learning, 2022

A Langevin-like Sampler for Discrete Distributions.

Ruqi Zhang, Xingchao Liu, Qiang Liu

Proceedings of the International Conference on Machine Learning, 2022

2021

Meta-Learning Divergences for Variational Inference.

Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Meta-Learning for Variational Inference.

Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

CoRR, 2020

Asymptotically Optimal Exact Minibatch Metropolis-Hastings.

Ruqi Zhang, A. Feder Cooper, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning.

Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson

Proceedings of the 8th International Conference on Learning Representations, 2020

AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC.

Ruqi Zhang, A. Feder Cooper, Christopher De Sa

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees.

Ruqi Zhang, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Acupoint Selection Rule Mining of Premature Ovarian Failure Treatment with Acupuncture and Moxibustion Based on the Data Analysis of Clinical Literature.

Xiaochun Han, Yanni Fan, Haijun Zhao, Shijun Wang, Sisheng Tian, Hongyuan Zhang, Zhe Yang, Ruqi Zhang, Jing Zhang, Wei Shi

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2016

Large Scale Sparse Clustering.

Ruqi Zhang, Zhiwu Lu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Denoising Cluster Analysis.

Ruqi Zhang, Zhirong Yang, Jukka Corander

Proceedings of the Neural Information Processing - 22nd International Conference, 2015