Answer-Based Entity Extraction and Alignment for Visual Text Question Answering. - Jun Yu 001; Mohan Jing; Weihao Liu; Tongxu Luo; Bingyuan Zhang; Keda Lu; Fangyu Lei; Jianqing Sun; Jiaen Liang (ACM Multimedia, 2023)

MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images. - Weihao Liu; Fangyu Lei; Tongxu Luo; Jiahe Lei; Shizhu He; Jun Zhao 001; Kang Liu 001 (CoRR, 2023)

HRoT: Hybrid prompt strategy and Retrieval of Thought for Table-Text Hybrid Question Answering. - Tongxu Luo; Fangyu Lei; Jiahe Lei; Weihao Liu; Shizhu He; Jun Zhao 001; Kang Liu 001 (CoRR, 2023)

TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering. - Fangyu Lei; Tongxu Luo; Pengqi Yang; Weihao Liu; Hanwen Liu; Jiahe Lei; Yiming Huang; Yifan Wei 001; Shizhu He; Jun Zhao 001; Kang Liu 001 (CoRR, 2023)

Unlocking Continual Learning Abilities in Language Models. - Wenyu Du; Shuang Cheng; Tongxu Luo; Zihan Qiu; Zeyu Huang; Ka Chun Cheung; Reynold Cheng; Jie Fu 001 (EMNLP (Findings), 2024)

Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent. - Xiaoyan Yu; Tongxu Luo; Yifan Wei 001; Fangyu Lei; Yiming Huang; Hao Peng 001; Liehuang Zhu (EMNLP, 2024)

Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training. - Wenyu Du; Tongxu Luo; Zihan Qiu; Zeyu Huang; Yikang Shen; Reynold Cheng; Yike Guo; Jie Fu 001 (NeurIPS, 2024)

CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark. - Ge Zhang 009; Xinrun Du; Bei Chen; Yiming Liang; Tongxu Luo; Tianyu Zheng; Kang Zhu; Yuyang Cheng; Chunpu Xu; Shuyue Guo; Haoran Zhang; Xingwei Qu; et al. (CoRR, 2024)

MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models. - Tongxu Luo; Jiahe Lei; Fangyu Lei; Weihao Liu; Shizhu He; Jun Zhao 001; Kang Liu 001 (CoRR, 2024)

Learning from Peers in Reasoning Models. - Tongxu Luo; Wenyu Du; Jiaxi Bi; Stephen Chung; Zhengyang Tang; Hao Yang 006; Min Zhang; Benyou Wang (CoRR, 2025)