Hi! I'm Hao Li

Researcher at ERNIE Team, Baidu
Specialized in |
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Hao Li (李昊)

I‘m one of the select few members of technical staff @ ERNIE Team, Baidu driving the Reinforcement Learning and On-policy Distillation for our flagship model releases.

Prior to this, I was a Post-doc @ Imperial College London and Research Intern @ Microsoft Research

My research interests lie in Recursive Self-Improvement and Reinforcement Learning. Recently, focusing on:

  • Agentic RL & Reward Modeling
  • Recursive Self-Improvement
  • On-policy Distillation

Email / LinkedIn / Google Scholar / GitHub / CV

My Photo

Model Releases

ERNIE 5.1
ERNIE Team, Baidu
Primary contributor. Post-training and RL core recipe.
🏆 #1 in China (Text Arena) 🌎 #4 Globally (Search Arena) 🤗 768B LLM
[Product] [Blog]
ERNIE 5.0
ERNIE Team, Baidu
Co-author.
🏆 #1 in China (Text Arena) 🌎 #8 Globally 🤗 2.4T(2400B) LLM
[Product] [Blog] [Hugging Face] [Technical Report]

Selected Work

TimeCraft: A Controllable Generative Engine for Time-Series Data
Microsoft Research
🌟 Major AI Conference 📊 Diffusion Model
[GitHub] [Paper]

Selected Publications

Term2Note: Synthesising Differentially Private Clinical Notes from Medical Terms
Yuping Wu, Viktor Schlegel, Warren Del-Pinto, Srinivasan Nandakumar, Iqra Zahid, Yidan Sun, Hao Li, Usama Farghaly Omar, Amirah Jasmine, Arun-Kumar Kaliya-Perumal, Chun Shen Tham, Gabriel Connors, Anil A Bharath, Goran Nenadic
EMNLP 2026 Findings
[Paper]
MN-TSG: Continuous Time Series Generation with Irregular Observations
Xu Zhang, Junwei Deng, Chang Xu, Hao Li, Jiang Bian
ICML 2026
[Paper]
Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement
Hao Li, Yizheng Sun, Viktor Schlegel, Kailai Yang, Riza Batista-Navarro, Goran Nenadic
ACL 2026
[Paper]
Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training
Kailai Yang, Xiao Liu, Lei Ji, Hao Li, Yeyun Gong, Peng Cheng, Mao Yang
ACL 2026
[Paper]
MIRA: Medical Time Series Foundation Model for Real-World Health Data
Hao Li, Bowen Deng, Chang Xu, Zhiyuan Feng, Viktor Schlegel, Yu-Hao Huang, Yizheng Sun, Jingyuan Sun, Kailai Yang, Yiyao Yu, Jiang Bian
NeurIPS 2025
[Paper] [Code] [Talk]
BRIDGE: Bootstrapping Text to Control Time-series Generation via Multi-agent Iterative Optimization and Diffusion Modeling
Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian
ICML 2025
[Paper] [Code] [Talk]
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation
Bowen Deng, Chang Xu, Hao Li, Yu-Hao Huang, Min Hou, Jiang Bian
KDD 2025
[Paper] [Code] [Talk]
Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study
Yizheng Sun, Hao Li, Chang Xu, Hongpeng Zhou, Chenghua Lin, Riza Batista-Navarro, Jingyuan Sun
EMNLP 2025
[Paper]
LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models
Yizheng Sun, Yanze Xin, Hao Li, Jingyuan Sun, Chenghua Lin, Riza Batista-Navarro
NAACL 2025 Findings
[Paper]
Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation
Hao Li, Yuping Wu, Viktor Schlegel, Riza Batista-Navarro, Tharindu Madusanka, Iqra Zahid, Jiayan Zeng, Xiaochi Wang, Xinran He, Yizhi Li, Goran Nenadic
ACL 2024 Findings
[Paper] [Code]
CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of Large Language Models
Yizhi Li, Ge Zhang, Xingwei Qu, Jiali Li, Zhaoqun Li, Zekun Wang, Hao Li, Ruibin Yuan, Yinghao Ma, Kai Zhang, Wangchunshu Zhou, Yiming Liang, Lei Zhang, Lei Ma, Jiajun Zhang, Zuowen Li, Stephen W Huang, Chenghua Lin, Wenhu Chen, Jie Fu
ACL 2024 Findings
[Paper] [Code]
Do You Hear the People Sing? Key Point Analysis via Iterative Clustering and Abstractive Summarisation
Hao Li, Viktor Schlegel, Riza Theresa Batista-Navarro, Goran Nenadic
ACL 2023
[Paper] [Code]
Not All Quantifiers Are Equal: Probing Transformer-based Language Models' Understanding of Generalised Quantifiers
Tharindu Madusanka, Iqra Zahid, Hao Li, Ian Pratt-Hartmann, Riza Batista-Navarro
EMNLP 2023
[Paper]