Selected Publications

  • Qwen Team. (2023). Qwen Technical Report. arXiv.

  • Bai, J., Bai S., Yang, S., Wang, S., Tan, S., Wang, P., Lin, J., Zhou, C. & Zhou., J. (2023). Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond. arXiv.

  • Wang, P., Yang, A., Men, R., Lin, J., Bai, S., Li, Z., Ma, J., Zhou, C., Zhou, J., & Yang, H. (2022). Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework. ICML.

  • Bai, J., Men, R., Yang, H., Ren, X., Dang, K.E., Zhang, Y., Zhou, X., Wang, P., Tan, S., Yang, A., Cui, Z., Han, Y., Bai, S., Ge, W., Ma, J., Lin, J., Zhou, J., & Zhou, C. (2022). OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models. arXiv, abs/2212.04408.

  • Lin, J., Men, R., Yang, A., Zhou, C., Zhang, Y., Wang, P., Zhou, J., Tang, J., & Yang, H. (2021). M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. KDD.

  • Yang, A., Pan, J., Lin, J., Men, R., Zhang, Y., Zhou, J., & Zhou, C. (2022). Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese. arXiv, abs/2211.01335.

  • Ma, J., Bai, S., & Zhou, C. (2022). Pretrained Diffusion Models for Unified Human Motion Synthesis. arXiv, abs/2212.02837.

  • Yang, H., Lin, J., Yang, A., Wang, P., Zhou, C., & Yang, H. (2022). Prompt Tuning for Generative Multimodal Pretrained Models. arXiv, abs/2208.02532.

  • Zhou, X., Wang, J., Cui, Z., Zhang, S., Yan, Z., Zhou, J., & Zhou, C. (2022). MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition. arXiv, abs/2212.00500.

  • Huang, Y., Lin, J., Zhou, C., Yang, H., & Huang, L. (2022). Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably). ICML.

  • Bai, S., Zhou, H., Li, Z., Zhou, C., & Yang, H. (2022). Single Stage Virtual Try-on via Deformable Attention Flows. ECCV.

  • Cui, Z., Ma, J., Zhou, C., Zhou, J., Yang, H. (2022). M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems. arXiv, abs/2205.08084.

  • Zhang, Z., Ma, J., Zhou, C., Men, R., Li, Z., Ding, M., Tang, J., Zhou, J., & Yang, H. (2021). UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis. NeurIPS.

  • Lin, J., Yang, A., Bai, J., Zhou, C., Jiang, L., Jia, X., Wang, A., Zhang, J., Li, Y., Lin, W., Zhou, J., & Yang, H. (2021). M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining. arXiv, abs/2110.03888.

  • Yang, A., Lin, J., Men, R., Zhou, C., Jiang, L., Jia, X., Wang, A., Zhang, J., Wang, J., Li, Y., Zhang, D., Lin, W., Lin, Q., Zhou, J., & Yang, H. (2021). M6-T: Exploring sparse expert models and beyond. arXiv, abs/2105.15082.

  • Ding, M., Yang, Z., Hong, W., Zheng, W., Zhou, C., Yin, D., Lin, J., Zou, X., Shao, Z., Yang, H., & Tang, J. (2021). CogView: Mastering Text-to-Image Generation via Transformers. NeurIPS.

  • Ren, S., Lin, J., Zhao, G., Men, R., Yang, A., Zhou, J., Sun, X., & Yang, H. (2021). Learning Relation Alignment for Calibrated Cross-modal Retrieval. ACL-IJCNLP.

  • Wang, P., Lin, J., Yang, A., Zhou, C., Zhang, Y., Zhou, J., & Yang, H. (2021). Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation. Findings of ACL-IJCNLP.

  • Lin, J., Yang, A., Zhang, Y., Liu, J., Zhou, J., & Yang, H. (2020). InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining. arXiv, abs/2003.13198.

  • Zhang, Z., Zhou, C., Ma, J., Lin, Z., Zhou, J., Yang, H., & Zhao, Z. (2021). Learning to Rehearse in Long Sequence Memorization. ICML.

  • Zhou, C., Ma, J., Zhang, J., Zhou, J., & Yang, H. (2021). Contrastive learning for debiased candidate generation in large-scale recommender systems. KDD.

  • Ma, J., Zhou, C., Cui, P., Yang, H., & Zhu, W. (2019). Learning Disentangled Representations for Recommendation. NeurIPS.

  • Chen, Q., Lin, J., Zhang, Y., Ding, M., Cen, Y., Yang, H., & Tang, J. (2019). Towards Knowledge-Based Recommender Dialog System. EMNLP-IJCNLP.

  • Chen, Q., Lin, J., Zhang, Y., Yang, H., Zhou, J., & Tang, J. (2019). Towards Knowledge-Based Personalized Product Description Generation in E-commerce. KDD.