Yu, Lili

15 publications

CoRL 2025 $\pi_0.5$: A Vision-Language-Action Model with Open-World Generalization Kevin Black, Noah Brown, James Darpinian, Karan Dhabalia, Danny Driess, Adnan Esmail, Michael Robert Equi, Chelsea Finn, Niccolo Fusai, Manuel Y. Galliker, Dibya Ghosh, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, James Tanner, Quan Vuong, Homer Walke, Anna Walling, Haohuan Wang, Lili Yu, Ury Zhilinsky

NeurIPS 2025 CAT: Content-Adaptive Image Tokenization Junhong Shen, Kushal Tirumala, Michihiro Yasunaga, Ishan Misra, Luke Zettlemoyer, Lili Yu, Chunting Zhou

NeurIPS 2025 Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better Danny Driess, Jost Tobias Springenberg, Brian Ichter, Lili Yu, Adrian Li-Bell, Karl Pertsch, Allen Z. Ren, Homer Walke, Quan Vuong, Lucy Xiaoyang Shi, Sergey Levine

NeurIPS 2025 LMFusion: Adapting Pretrained Language Models for Multimodal Generation Weijia Shi, Xiaochuang Han, Chunting Zhou, Weixin Liang, Xi Victoria Lin, Luke Zettlemoyer, Lili Yu

ICLRW 2025 Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity Weixin Liang, Junhong Shen, Genghan Zhang, Ning Dong, Luke Zettlemoyer, Lili Yu

TMLR 2025 Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models Weixin Liang, Lili Yu, Liang Luo, Srini Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Xi Victoria Lin

ICLRW 2025 Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models Weixin Liang, Lili Yu, Liang Luo, Srini Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Xi Victoria Lin

ICLRW 2025 Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models Weixin Liang, Lili Yu, Liang Luo, Srini Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Xi Victoria Lin

ICLR 2025 Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, Omer Levy

ICLR 2024 Jointly Training Large Autoregressive Multimodal Models Emanuele Aiello, Lili Yu, Yixin Nie, Armen Aghajanyan, Barlas Oguz

NeurIPS 2024 Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou

NeurIPS 2023 LIMA: Less Is More for Alignment Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy

NeurIPS 2023 MEGABYTE: Predicting Million-Byte Sequences with Multiscale Transformers Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis

ICML 2023 Scaling Laws for Generative Mixed-Modal Language Models Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer

AAAI 2021 Nutri-Bullets: Summarizing Health Studies by Composing Segments Darsh J. Shah, Lili Yu, Tao Lei, Regina Barzilay