About Me

I am a second-year Ph.D. student at the University of Maryland, College Park, advised by Prof. Heng Huang. Previously, I worked as a research assistant at the Natural Language Processing Laboratory of Northeastern University (China), supervised by Prof. Tong Xiao. I received my B.E. degree from Northeastern University of Computer Science and Engineering in 2021.

My research is driven by a core vision: to build AI that is both fundamentally intelligent and universally accessible. I focus on creating novel paradigms that unlock the full potential of (large) language models, covering three key areas:

  • Efficient Backbone/Foundation Model: Multi-scale Modeling (UMST, ICML2022), Subspace Interaction (EIT, ACL2024), Subspace Modeling (PartialFormer, ACL2024), ODE (PCFormer, NeurIPS2024), Encode-Decoder Trade-offs (LaMaTE, ACL2025)
  • Efficient Training and Inference Strategies: Multi-Draft Speculative Decoding (ICLR2025), Asymmetric Training for MMT (ACL2025), Self-evolving Training (ICLR2026)
  • Next-Generation Reasoning Paradigms: Developing scalable RL frameworks for efficient parallel reasoning, such as Formal-Informal Language Co-Evolving Training and inference (ICLR2026), Parallel Thinking (ICLR2026)

News

Jan. 2026
Three papers accepted for publication at ICLR 2026.
Oct. 2025
Check our new papers for VLM exploration: VOGUE: visual uncertainty guied exploration.
Seq 2025
Check our new papers for LLM reasoning: Parallel-R1: First RL framework to teach LLMs Parallel Thinking for real-world tasks; and CDE: Curiosity-Driven Exploration for RLVR.
Aug 20 2025
One paper accepted for publication at EMNLP2025 2025.
May 15 2025
Two papers accepted for publication at ACL 2025 findings.
Feb 10 2025
I will join Tencent AI Lab (Seattle) as a research intern this summar.
Jan. 22 2025
One paper accepted for publication at ICLR 2025.
Sep. 25 2024
One paper accepted for publication at NIPS 2024.
Sep. 19 2024
One paper accepted for publication at EMNLP2024 Main Conference.
Aug. 19 2024
Start my PhD study at University of Maryland, College Park.
May. 16 2024
Two papers accepted for publication at ACL2024 (1 Main, 1 Findings).
Oct. 8 2023
One paper accepted for publication at Findings of EMNLP2023.
May. 14 2022
"Learning Multiscale Transformer Models for Sequence Generation" accepted for publication at ICML 2022. (First ICML in NEUNLP)
Sep. 1 2021
Join in NEUNLP lab as a research assistant.
Jun. 25 2021
Graduate from Northeastern University with an average GPA of 4.0.

Pre-prints (* Equal Contribution)

NEW 🔥 VOGUE: Guiding Exploration with Visual Uncertainty Improves Multimodal Reasoning [paper]
Arxiv, 2025
Rui Liu, Dian Yu, Tong Zheng, Runpeng Dai, Zongxia Li, Wenhao Yu, Zhenwen Liang, Linfeng Song, Haitao Mi, Pratap Tokekar, Dong Yu

Selected Publications (* Equal Contribution)

NEW 🔥 Parallel-R1: Towards Parallel Thinking via Reinforcement Learning [paper][Project Website]
ICLR 2026 Main Conference; Neurips ER Workshop Spotlight
Tong Zheng, Hongming Zhang, Wenhao Yu, Xiaoyang Wang, Xinyu Yang, Runpeng Dai, Rui Liu, Huiwen Bao, Chengsong Huang, Heng Huang, Dong Yu
NEW 🔥 Learning to Reason via Mixture-of-Thought for Logical Reasoning [paper]
ICLR 2026 Main Conference; Neurips ER Workshop
Tong Zheng*, Lichang Chen*, Simeng Han, R. Thomas McCoy, Heng Huang.
NEW 🔥 CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models [paper]
ICLR 2026 Main Conference; Neurips MATH-AI Workshop
Runpeng Dai, Linfeng Song, Haolin Liu, Zhenwen Liang, Dian Yu, Haitao Mi, Zhaopeng Tu, Rui Liu, Tong Zheng, Hongtu Zhu, Dong Yu
Asymmetric Conflict and Synergy in Post-training for LLM-based Multilingual Machine Translation [paper]
ACL findings, 2025
Tong Zheng, Yan Wen, Huiwen Bao, Junfeng Guo, Heng Huang.
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine Translation [paper]
ACL findings, 2025
Yingfeng Luo, Tong Zheng, Yongyu Mu, Bei Li, Qinghong Zhang, Yongqi Gao, Ziqiang Xu, Peinan Feng, Xiaoqian Liu, Tong Xiao, Jingbo Zhu.
Towards Optimal Multi-draft Speculative Decoding.
ICLR2025
Zhengmian Hu*, Tong Zheng*, Vignesh Viswanathan, Ziyi Chen, Ryan A. Rossi, Yihan Wu, Dinesh Manocha, Heng Huang
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning.
Neurips2024
Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Qingyan Guo, Junliang Guo, Xu Tan, Tong Xiao, Jingbo Zhu, Jingang Wang, Xunliang Cai
A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution.
EMNLP2024 Main
Zhengmian Hu*, Tong Zheng*, Heng Huang
PartialFormer: Modeling Part Instead of Whole. [Paper]
ACL2024 Findings
Tong Zheng*, Bei Li*, Huiwen Bao*, Weiqiao Shan, Tong Xiao, Jingbo Zhu
EIT: Enhanced Interactive Transformer. [Paper]
ACL2024 Main Conference
Tong Zheng*, Bei Li*, Huiwen Bao*, Tong Xiao, Jingbo Zhu
Learning Multiscale Transformer Models for Sequence Generation. [Paper]
ICML 2022
Bei Li*, Tong Zheng*, Yi Jing*, Chengbo Jiao, Tong Xiao, Jingbo Zhu

Manuscript

BrainTGL: Temporal Graph representation learning for brain network by Exploiting Graph Temporal Information. [Manuscript]
Finished at August 2021
Tong Zheng

Selected Honors

UMD Dean's Fellowship, 2024-2026.
Adapted from template.