publications

Papers and preprints, newest first.

2026

  1. RSI Arena: Towards Recursive Self-Improvement with Human Feedback
    Yue Huang, Yanbo Wang, Lichi Li, Yuanyuan Chen, Andreas Haupt, Xiaonan Luo, Zheyuan Liu, Jihye Choi, Felix Juefei-Xu, Xiangliang Zhang, Radha Poovendran, Misha Sra, Ying Liu, Ben Burtenshaw, Thomas Wolf, and 3 more authors
    arXiv preprint arXiv:2610.33624, Oct 2026
  2. BARC-Bench: Benign Asks, Risky Consequences
    Kangkang Li, Kelvin Luu, Lily Ma, Tu Trinh, Ying Liu, and Mohamed Elfeki
    arXiv preprint arXiv:2610.32024, Oct 2026
  3. Epi: Towards a Persistent, Self-Improving Agent for Autonomous Research
    Yue Huang, Zhangchen Xu, Xiaonan Luo, Zheyuan Liu, Lichi Li, Yiping Wang, Peiyang Song, Eric Gabriel Ramos, Enze Xie, Olexandr Isayev, Paul Liang, Nouha Dziri, Huan Sun, Jianfeng Gao, Ying Liu, and 4 more authors
    arXiv preprint arXiv:2610.24944, Oct 2026
  4. Maintaining Benchmarks Against Increasingly Capable Agents: Detection and Remediation of Unearned Passes
    Weijun Luo, Kelvin Luu, Xinyi Liu, Guangze Luo, Miguel Romero Calvo, Soham Dan, Daniel Yue Zhang, Ying Liu, and Mohamed Elfeki
    arXiv preprint arXiv:2609.34262, Sep 2026
  5. READY or Not: Reliable Enterprise Agent Deployment
    Veronica Chatrath, Bryan Zhu, Jingxuan Fan, George Pu, Soham Dinesh Tiwari, Soham Dan, Ryan Young, Yuan Li, Yuang Yao, Apaar Shanker, Minglai Yang, Daniel Yue Zhang, Yunzhong He, Ying Liu, Chenguang Wang, and 2 more authors
    arXiv preprint arXiv:2609.02095, Sep 2026
  6. Spine-Branch Coordination for Multi-agent Computer Use
    Mian Zhang, Manasi Sharma, Sheng Zhang, Minglai Yang, Kejian Shi, Ying Liu, Zhiyu Zoey Chen, and Daniel Yue Zhang
    arXiv preprint arXiv:2608.22077, Aug 2026
  7. Rubric Dropout: A Simple Way to Mitigate Reward Hacking in Rubric-as-Reward RL
    Minglai Yang, Xinyu Guo, Utkarsh Tyagi, Mian Zhang, Razvan Dumitru, Sunjie Hou, Yunzhong He, Daniel Yue Zhang, and Ying Liu
    arXiv preprint arXiv:2608.11669, Aug 2026
  8. Preprint
    Agentic Laboratories of the Future: Towards World Models for Scientific Discovery
    Kelsey Fu, Luna Lyu, Shuzhen Li, Suozhi Huang, Suheng Xu, Joy Zheng, Xuefeng Liu, Shilong Liu, Greg Barbone, Ying Liu, Linxi Jim Fan, Yuke Zhu, Matthew Davis, Kaiyi Jiang, Sherry Yang, and 40 more authors
    Preprints.org, Aug 2026
  9. Report
    DrugDiscoveryBench: Can Coding Agents Assist Early-Stage Drug Discovery?
    Afra Feyza Akyürek, Xinming Tu, Alec Gutmanstein, Jason Qin, Divyansh Agarwal, Sofia Monasdotter, Sergey Chekhov, Brenda Hernandez Villegas, Kirill Chugunov, Judah Engel, Veronica Chatrath, Oscar Kavanagh, Geobio Boo, Ernesto Hernandez, Ying Liu, and 7 more authors
    Scale AI technical report, with Phylo , Jun 2026
  10. ChainWorld: Composing Long-Horizon Desktop Workloads from Atomic OSWorld Tasks
    Vincent Siu, Manasi Sharma, Dawn Song, Daniel Yue Zhang, Chenguang Wang, and Ying Liu
    arXiv preprint arXiv:2606.21654, Jun 2026
  11. TLX: Hardware-Native, Evolvable MIMW GPU Compiler for Large-scale Production Environments
    Yue Guan, Hongtao Yu, Peng Chen, Daohang Shi, Karthik Manivannan, Nicholas J. Riasanovsky, Manman Ren, Lei Wang, Shane Nay, Partha Kanuparthy, Zhijing Li, Ying Liu, Zaifeng Pan, Zhengding Hu, and Yufei Ding
    arXiv preprint arXiv:2605.10905, May 2026

2015

  1. Sampling from Gaussian Markov Random Fields Using Stationary and Non-Stationary Subgraph Perturbations
    Ying Liu, Oliver Kosut, and Alan S. Willsky
    IEEE Transactions on Signal Processing, 2015

2013

  1. Learning Gaussian Graphical Models with Observed or Latent FVSs
    Ying Liu and Alan S. Willsky
    In Advances in Neural Information Processing Systems (NeurIPS), 2013
  2. Recursive FMP for Distributed Inference in Gaussian Graphical Models
    Ying Liu and Alan S. Willsky
    In IEEE International Symposium on Information Theory (ISIT), 2013
  3. Sampling from Gaussian Graphical Models Using Subgraph Perturbations
    Ying Liu, Oliver Kosut, and Alan S. Willsky
    In IEEE International Symposium on Information Theory (ISIT), 2013

2012

  1. Feedback Message Passing for Inference in Gaussian Graphical Models
    Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, and Alan S. Willsky
    IEEE Transactions on Signal Processing, 2012

2011

  1. FaST Linear Mixed Models for Genome-Wide Association Studies
    Christoph Lippert, Jennifer Listgarten, Ying Liu, Carl M. Kadie, Robert I. Davidson, and David Heckerman
    Nature Methods, 2011

2010

  1. Feedback Message Passing for Inference in Gaussian Graphical Models
    Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, and Alan S. Willsky
    In IEEE International Symposium on Information Theory (ISIT), 2010

2008

  1. Automatic Mining of Vehicle Behaviors with an Unknown Number of Categories
    Ying Liu, Hao Zhang, Huadong Meng, and Xiqin Wang
    In IEEE International Conference on Intelligent Transportation Systems (ITSC), Oct 2008

2007

  1. THU and ICRC at TRECVID 2007
    Jinhui Yuan, Zhishan Guo, Li Lv, Wei Wan, Teng Zhang, Dong Wang, Xiaobing Liu, Cailiang Liu, Shengqi Zhu, Duanpeng Wang, Yang Pang, Nan Ding, Ying Liu, Jiangping Wang, Xiujun Zhang, and 15 more authors
    In TREC Video Retrieval Evaluation (TRECVID) Workshop, Nov 2007
    Notebook paper; joint entry of Tsinghua University and Intel China Research Center