I'm a second-year Ph.D. student in Computer Science at the University of Illinois Urbana-Champaign, advised by
Hanghang Tong.
Previously, I earned my bachelor's degree from Fudan University.
My current research interests center on new ways to design and train language models, with the goal of improving reasoning, generation efficiency, and the ability to benefit from more data and compute.
My current work focuses on diffusion language models, particularly how iterative refinement and parallel generation can advance these goals and complement existing language models and their training and serving infrastructure.
Feel free to reach out to discuss research, explore collaborations, or just to say hello!
Email: lingjie7 [at] illinois [dot] edu
Publications
Unlocking Lossless Speedups in LLMs via Discrete Diffusion
Subham Sekhar Sahoo*, Lingjie Chen*, Khiem Pham*, Jonathan Geuter*, Chaitanya Dwivedi, Varad Pimpalkhute, Yash Akhauri, Alexander Moreno, Mikhail Yurochkin, Zhenting Wang, Mostafa Elhoushi, Nolan Dey, Shane Bergsma, Joel Hestness, John Thickstun, Eric Xing, Zhengzhong Liu * Core contributors arXiv 2026
@misc{uno2026,
title={Unlocking Lossless Speedups in LLMs via Discrete Diffusion},
author={Subham Sekhar Sahoo and Lingjie Chen and Khiem Pham and Jonathan Geuter and Chaitanya Dwivedi and Varad Pimpalkhute and Yash Akhauri and Alexander Moreno and Mikhail Yurochkin and Zhenting Wang and Mostafa Elhoushi and Nolan Dey and Shane Bergsma and Joel Hestness and John Thickstun and Eric Xing and Zhengzhong Liu},
year={2026},
eprint={2609.04010},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2609.04010}
}
@misc{trims2026,
title={TRIMS: Trajectory-Ranked Instruction Masked Supervision for Diffusion Language Models},
author={Lingjie Chen and Ruizhong Qiu and Yuyu Fan and Yanjun Zhao and Hanghang Tong},
year={2026},
eprint={2604.00666},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2604.00666}
}
@inproceedings{zhou-etal-2026-dllm,
title={dLLM: Simple Diffusion Language Modeling},
author={Zhanhui Zhou and Lingjie Chen and Hanghang Tong and Dawn Song},
booktitle={Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)},
year={2026},
pages={78--88},
doi={10.18653/v1/2026.acl-demo.8},
url={https://aclanthology.org/2026.acl-demo.8/}
}
@misc{he2024llamascope,
title={Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders},
author={Zhengfu He and Wentao Shu and Xuyang Ge and Lingjie Chen and Junxuan Wang and Yunhua Zhou and Frances Liu and Qipeng Guo and Xuanjing Huang and Zuxuan Wu and Yu-Gang Jiang and Xipeng Qiu},
year={2024},
eprint={2410.20526},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2410.20526}
}
A toolkit for mechanistic interpretability, supporting sparse autoencoder training and evaluation alongside interactive exploration of learned features.
