Yutong Wang, Jiali Zeng, Xuebo Liu, Derek F. Wong, Fandong Meng, Jie Zhou, Min Zhang. 2025. DelTA: An Online Document-Level Translation Agent Based on Multi-Level Memory. In Proceedings of ICLR 2025. [paper][code]
Yifan Lu, Yigeng Zhou, Jing Li, Yequan Wang, Xuebo Liu, Daojing He, Fangming Liu, Min Zhang. 2025. Knowledge Editing with Dynamic Knowledge Graphs for Multi-hop Question Answering. In Proceedings of AAAI 2025. [paper]
Junchao Wu, Runzhe Zhan, Derek F. Wong, Shu Yang, Xuebo Liu, Lidia S. Chao, Min Zhang. 2025. Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore. In Proceedings of COLING 2025. [paper]
2024
Jiaqi Zhao, Miao Zhang, Chao Zeng, Ming Wang, Xuebo Liu, Liqiang Nie. 2024. LRQuant: Learnable and Robust Post-Training Quantization for Large Language Models. In Proceedings of ACL 2024. [paper][code]
Tengfei Yu, Xuebo Liu, Liang Ding, Kehai Chen, Dacheng Tao, Min Zhang. 2024. Speech Sense Disambiguation: Tackling Homophone Ambiguity in End-to-End Speech Translation. In Proceedings of ACL 2024. [paper][code]
Yutong Wang, Jiali Zeng, Xuebo Liu, Fandong Meng, Jie Zhou, Min Zhang. 2024. TasTe: Teaching Large Language Models to Translate through Self-Reflection. In Proceedings of ACL 2024. [paper][code]
Keqin Peng, Liang Ding, Yancheng Yuan, Xuebo Liu, Min Zhang, Yuanxin Ouyang, Dacheng Tao. 2024. Revisiting Demonstration Selection Strategies in In-Context Learning. In Proceedings of ACL 2024. [paper][code]
Chen Li, Meishan Zhang, Xuebo Liu, Zhaocong Li, Derek F. Wong, Min Zhang. 2024. Towards Demonstration-Aware Large Language Models for Machine Translation. In Proceedings of ACL 2024 Findings. [paper][code]
Zhexuan Wang, Shudong Liu, Xuebo Liu, Miao Zhang, Derek F. Wong, Min Zhang. 2024. Domain-Aware k-Nearest-Neighbor Knowledge Distillation for Machine Translation. In Proceedings of ACL 2024 Findings. [paper][code]
Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu. 2024. DB-LLM: Accurate Dual-Binarization for Efficient LLMs. In Proceedings of ACL 2024 Findings. [paper]
Dongfang Li, Zetian Sun, Baotian Hu, Zhenyu Liu, Xinshuo Hu, Xuebo Liu, Min Zhang. 2024. Improving Attributed Text Generation of Large Language Models via Preference Learning. In Proceedings of ACL 2024 Findings. [paper]
Jun Rao, Xuebo Liu, Lian Lian, Shengjun Cheng, Yunjie Liao, Min Zhang. 2024. CommonIT: Commonality-aware Instruction Tuning for Large Language Models via Data Partitions. In Proceedings of EMNLP 2024. [paper][code]
Shudong Liu, Zhaocong Li, Xuebo Liu, Runzhe Zhan, Derek F. Wong, Lidia S. Chao, Min Zhang. 2024. Can LLMs Learn Uncertainty on Their Own? Expressing Uncertainty Effectively in A Self-Training Manner. In Proceedings of EMNLP 2024. [paper]
Liangxin Liu, Xuebo Liu, Lian Lian, Shengjun Cheng, Jun Rao, Tengfei Yu, Hexuan Deng, Min Zhang. 2024. Curriculum Consistency Learning for Conditional Sentence Generation. In Proceedings of EMNLP 2024. [paper][code]
Tengfei Yu, Xuebo Liu, Zhiyi Hou, Liang Ding, Dacheng Tao, Min Zhang. 2024. Self-Powered LLM Modality Expansion for Large Speech-Text Models. In Proceedings of EMNLP 2024. [paper][code]
Peijie Dong, Lujun Li, Xiang Liu, Zhenheng Tang, Xuebo Liu, Qiang Wang, Xiaowen Chu. 2024. LPZero: Language Model Zero-cost Proxy Search from Zero. In Proceedings of EMNLP 2024 Findings. [paper]
Liangxin Liu, Xuebo Liu, Derek F. Wong, Dongfang Li, Ziyi Wang, Baotian Hu, Min Zhang. 2024. SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection. In Proceedings of NeurIPS 2024. [paper][code]
Hexuan Deng, Wenxiang Jiao, Xuebo Liu, Min Zhang, Zhaopeng Tu. 2024. NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates. In Proceedings of NeurIPS 2024 Datasets and Benchmarks Track. [paper][code]
Yaofang Liu, Xiaodong Cun, Xuebo Liu, Xintao Wang, Yong Zhang, Haoxin Chen, Yang Liu, Tieyong Zeng, Raymond Chan, Ying Shan. 2024. EvalCrafter: Benchmarking and Evaluating Large Video Generation Models. In Proceedings of CVPR 2024. [paper][code]
Yuzhuang Xu, Shuo Wang, Peng Li, Xuebo Liu, Xiaolong Wang, Weidong Liu, Yang Liu. 2024. Pluggable Neural Machine Translation Models via Memory-augmented Adapters. In Proceedings of COLING 2024. [paper][code]
Xinyu Ma, Xuebo Liu, Derek F. Wong, Jun Rao, Bei Li, Liang Ding, Lidia S. Chao, Dacheng Tao, Min Zhang. 2024. 3AM: An Ambiguity-Aware Multimodal Machine Translation Dataset. In Proceedings of COLING 2024. [paper][code]
Yanming Sun, Xuebo Liu, Derek F. Wong, Yuchu Lin, Bei Li, Runzhe Zhan, Lidia S. Chao, Min Zhang. 2024. Understanding and Improving Low-Resource Neural Machine Translation with Shallow Features. In Proceedings of NLPCC 2024. [paper]
Hexuan Deng, Xin Zhang, Meishan Zhang, Xuebo Liu, Min Zhang. 2024. Holistic Exploration on Universal Decompositional Semantic Parsing: Architecture, Data augmentation, and LLM Paradigm. In Proceedings of ACL 2024 Workshop (SIGHAN-10). [paper][code]
2023
Runzhe Zhan, Xuebo Liu, Derek F. Wong, Cuilian Zhang, Lidia S. Chao, Min Zhang. 2023. Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization. In Proceedings of ACL 2023. [paper][code]
Qihuang Zhong, Liang Ding, Juhua Liu, Xuebo Liu, Min Zhang, Bo Du, Dacheng Tao. 2023. Revisiting Token Dropping Strategy in Efficient BERT Pretraining. In Proceedings of ACL 2023. [paper]
Shudong Liu, Xuebo Liu, Derek F. Wong, Zhaocong Li, Wenxiang Jiao, Lidia S. Chao, Min Zhang. 2023. kNN-TL: k-Nearest-Neighbor Transfer Learning for Low-Resource Neural Machine Translation. In Proceedings of ACL 2023. [paper][code]
Xuebo Liu, Yutong Wang, Derek F. Wong, Runzhe Zhan, Liangxuan Yu, Min Zhang. 2023. Revisiting Commonsense Reasoning in Machine Translation: Training, Evaluation and Challenge. In Proceedings of ACL 2023. [paper][code]
Yinghao Li, Xuebo Liu, Shuo Wang, Peiyuan Gong, Derek F. Wong, Yang Gao, He-Yan Huang, Min Zhang. 2023. TemplateGEC: Improving Grammatical Error Correction with Detection Template. In Proceedings of ACL 2023. [paper][code]
Tao Fang, Xuebo Liu, Derek F. Wong, Runzhe Zhan, Liang Ding, Lidia S. Chao, Dacheng Tao, Min Zhang. 2023. TransGEC: Improving Grammatical Error Correction with Translationese. In Proceedings of ACL 2023 Findings. [paper][code]
Xinyu Ma, Xuebo Liu, Min Zhang. 2023. Clustering Pseudo Language Family in Multilingual Translation Models with Fisher Information Matrix. In Proceedings of EMNLP 2023. [paper][code]
Tengfei Yu, Liang Ding, Xuebo Liu, Kehai Chen, Meishan Zhang, Dacheng Tao, Min Zhang. 2023. PromptST: Abstract Prompt Learning for End-to-End Speech Translation. In Proceedings of EMNLP 2023. [paper][code]
Chi Cheang, Hou Chan, Derek F. Wong, Xuebo Liu, Zhaocong Li, Yanming Sun, Shudong Liu, Lidia S. Chao. 2023. Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization. In Proceedings of EMNLP 2023. [paper][code]
Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, Dacheng Tao. 2023. Towards Making The Most of ChatGPT for Machine Translation. In Proceedings of EMNLP 2023 Findings. [paper][code]
Hexuan Deng, Liang Ding, Xuebo Liu, Meishan Zhang, Dacheng Tao, Min Zhang. 2022. Improving Simultaneous Machine Translation with Monolingual Data. In Proceedings of AAAI 2023. [paper][code]
Jun Rao, Xv Meng, Liang Ding, Shuhan Qi, Xuebo Liu, Min Zhang, Dacheng Tao. 2023. Parameter-Efficient and Student-Friendly Knowledge Distillation. In Proceedings of IEEE Transactions on Multimedia. [paper]
2022
Bei Li, Quan Du, Tao Zhou, Yi Jing, Shuhan Zhou, Xin Zeng, Tong Xiao, JingBo Zhu, Xuebo Liu, Min Zhang. 2022. ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation. In Proceedings of ACL 2022. [paper]
Zhijun Wang, Xuebo Liu, Min Zhang. 2022. Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence Modeling. In Proceedings of EMNLP 2022. [paper][code]
Peiyuan Gong, Xuebo Liu, Heyan Huang, Min Zhang. 2022. Revisiting Grammatical Error Correction Evaluation and Beyond. In Proceedings of EMNLP 2022. [paper][code]
Zhaocong Li, Xuebo Liu, Derek F. Wong, Lidia S. Chao, Min Zhang. 2022. ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation. In Proceedings of EMNLP 2022. [paper][code]
2021
Runzhe Zhan, Xuebo Liu, Derek F. Wong, Lidia S. Chao. 2021. Difficulty-Aware Machine Translation Evaluation. In Proceedings of ACL 2021. [paper][code]
Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu. 2021. Rejuvenating Low-Frequency Words: Making the Most of Parallel Data in Non-Autoregressive Translation. In Proceedings of ACL 2021. [paper][code]
Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Shuming Shi, Zhaopeng Tu. 2021. On the Copying Behaviors of Pre-Training for Neural Machine Translation. In Proceedings of ACL 2021 Findings. [paper][code]
Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu. 2021. Progressive Multi-Granularity Training for Non-Autoregressive Translation. In Proceedings of ACL 2021 Findings. [paper]
Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Shuming Shi, Zhaopeng Tu. 2021. On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation. In Proceedings of EMNLP 2021 Findings. [paper][code]
Chongman Leong, Xuebo Liu, Derek F. Wong, Lidia S. Chao. 2021. Exploiting Translation Model for Parallel Corpus Mining. In Proceedings of IEEE/ACM Transactions on Audio, Speech, and Language Processing. [paper]
Runzhe Zhan, Xuebo Liu, Derek F. Wong, Lidia S. Chao. 2021. Variance-Aware Machine Translation Test Sets. In Proceedings of NeurIPS 2021 Datasets and Benchmarks Track. [paper][code]
Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Zhaopeng Tu. 2021. Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning. In Proceedings of ICLR 2021. [paper][code]
Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu. 2021. Understanding and Improving Lexical Choice in Non-Autoregressive Translation. In Proceedings of ICLR 2021. [paper][code]
Runzhe Zhan, Xuebo Liu, Derek F. Wong, Lidia S. Chao. 2021. Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation. In Proceedings of AAAI 2021. [paper][code]
Until 2020
Xuebo Liu, Houtim Lai, Derek F. Wong, Lidia S. Chao. 2020. Norm-Based Curriculum Learning for Neural Machine Translation. In Proceedings of ACL 2020. [paper][code]
Xuebo Liu, Derek F. Wong, Yang Liu, Lidia S. Chao, Tong Xiao, Jingbo Zhu. 2019. Shared-Private Bilingual Word Embeddings for Neural Machine Translation. In Proceedings of ACL 2019. [paper]
Xuebo Liu, Derek F. Wong, Lidia S. Chao, Yang Liu. 2019. Latent Attribute Based Hierarchical Decoder for Neural Machine Translation. In Proceedings of IEEE/ACM Transactions on Audio, Speech, and Language Processing. [paper]