TaiMing Lu

I am a first year PhD student at Princeton University pton, advised by Zhuang Liu.

Previously, I was an undergraduate student at Johns Hopkins University GO HOP!, majoring in Computer Science, Applied Math and Stats, and Economics. At Hopkins, I was fortunate to work closely with Jieneng Chen and to be advised by Prof. Daniel Khashabi, Phillip Koehn, and Alan Yuille.

I research Generative Foundation Models (e.g., LLMs, VLMs, Diffusion Models) and explore their possibilities. My interest spans Machine Learning, Natural Language Processing, and Computer Vision.

Google Scholar  /  Semantic Scholar  /  Twitter  /  Github   
taiminglu@princeton.edu | tlu37@jhu.edu

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@EMNLP 2024

News
  • Selected Michael J. Muuss Undergraduate Research Award at JHU 🎇.
  • Genex accepted by ICLR 🥳.
  • Selected Finalist for CRA's Outstanding Undergraduate Researcher Award 🫡.
  • GenEx (Generative World Explorer) is on arXiv! View our demo on project website or YouTube Gnerative an Explorable World !
  • Poster presentation at EMNLP 🥸.

Publications
GenEx: Generating an Explorable World
Taiming Lu, Tianmin Shu, Junfei Xiao, Luoxin Ye, Jiahao Wang, Cheng Peng, Chen Wei, Daniel Khashabi, Rama Chellappa, Alan Yuille, Jieneng Chen
ICLR 2025    Paper | Code | Project | Video | Poster
Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell
Taiming Lu, Muhan Gao, Kuai Yu, Adam Byerly, Daniel Khashabi
EMNLP 2024 (Findings)    Paper | Code | Poster
Learn and Unlearn: Addressing Misinformation in Multilingual LLMs
Taiming Lu, Philipp Koehn
EMNLP 2025    Paper | Code | Data
It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF
Taiming Lu, Lingfeng Shen, Xinyu Yang, Weiting Tan, Beidi Chen, Huaxiu Yao
ICML 2024 Workshop on Foundation Models in the Wild    Paper | Code

Others