Liu, Zhengzhong

Efficient (Soft) Q-Learning for Text Generation with Limited Good Data

Guo, H., Tan, B., Liu, Z., Xing, E. P., & Hu, Z. (2021) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 20

Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs

Yun, S., Lin, H., Thushara, R., Bhat, M. Q., Wang, Y., Jiang, Z., Deng, M., Wang, J., Tao, T., Li, J., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsSoftware Engineering Research

Cited by 8

LLM360: Towards Fully Transparent Open-Source LLMs

Liu, Z., Qiao, A., Neiswanger, W., Wang, H., Tan, B., Tao, T., Li, J., Wang, Y., Sun, S., Pangarkar, O., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

Pandora: Towards General World Model with Natural Language Actions and Video States

Xiang, J., Liu, G., Gu, Y., Gao, Q., Ning, Y., Zha, Y., Feng, Z., Tao, T., Hao, S., Shi, Y., et al. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1

MegaMath: Pushing the Limits of Open Math Corpora

Zhou, F., Wang, Z., Ranjan, N., Cheng, Z., Tang, L., He, G., Liu, Z., & Xing, E. P. (2025) · arXiv

Topic ModelingMathematics, Computing, and Information Processing

Cited by 0