Liang Ding

According to our database, Liang Ding authored at least 117 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks.

Chuang Liu, Xueqi Ma, Yibing Zhan, Liang Ding, Dapeng Tao, Bo Du, Wenbin Hu, Danilo P. Mandic

IEEE Trans. Neural Networks Learn. Syst., October, 2024

Free-Form Composition Networks for Egocentric Action Recognition.

Haoran Wang, Qinghua Cheng, Baosheng Yu, Yibing Zhan, Dapeng Tao, Liang Ding, Haibin Ling

IEEE Trans. Circuits Syst. Video Technol., October, 2024

PanDa: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

IEEE Trans. Knowl. Data Eng., September, 2024

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, Dacheng Tao

Neural Networks, January, 2024

Parameter-Efficient and Student-Friendly Knowledge Distillation.

Jun Rao, Xv Meng, Liang Ding, Shuhan Qi, Xuebo Liu, Min Zhang, Dacheng Tao

IEEE Trans. Multim., 2024

Exploring sparsity in graph transformers.

Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu, Bo Du

Neural Networks, 2024

MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators.

Qingyu Lu, Liang Ding, Kanjian Zhang, Jinxia Zhang, Dacheng Tao

CoRR, 2024

Exploring and Enhancing the Transfer of Distribution in Knowledge Distillation for Autoregressive Language Models.

Jun Rao, Xuebo Liu, Zepeng Lin, Liang Ding, Jing Li, Dacheng Tao, Min Zhang

CoRR, 2024

USCD: Improving Code Generation of LLMs by Uncertainty-Aware Selective Contrastive Decoding.

Shuai Wang, Liang Ding, Li Shen, Yong Luo, Zheng He, Wei Yu, Dacheng Tao

CoRR, 2024

Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models.

Wenbin Wang, Liang Ding, Minyan Zeng, Xiabin Zhou, Li Shen, Yong Luo, Dacheng Tao

CoRR, 2024

Aligning Large Language Models from Self-Reference AI Feedback with one General Principle.

Rong Bao, Rui Zheng, Shihan Dou, Xiao Wang, Enyu Zhou, Bo Wang, Qi Zhang, Liang Ding, Dacheng Tao

CoRR, 2024

Demystifying the Compression of Mixture-of-Experts Through a Unified Framework.

Shwai He, Daize Dong, Liang Ding, Ang Li

CoRR, 2024

Improving Complex Reasoning over Knowledge Graph with Logic-Aware Curriculum Tuning.

Tianle Xia, Liang Ding, Guojia Wan, Yibing Zhan, Bo Du, Dacheng Tao

CoRR, 2024

Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Reasoners.

Qihuang Zhong, Kang Wang, Ziyang Xu, Juhua Liu, Liang Ding, Bo Du, Dacheng Tao

CoRR, 2024

Building Accurate Translation-Tailored LLMs with Language Aware Instruction Tuning.

Changtong Zan, Liang Ding, Li Shen, Yibing Zhen, Weifeng Liu, Dacheng Tao

CoRR, 2024

Towards Training A Chinese Large Language Model for Anesthesiology.

Zhonghai Wang, Jie Jiang, Yibing Zhan, Bohao Zhou, Yanhong Li, Chong Zhang, Liang Ding, Hua Jin, Jun Peng, Xu Lin, Weifeng Liu

CoRR, 2024

Balanced Similarity with Auxiliary Prompts: Towards Alleviating Text-to-Image Retrieval Bias for CLIP in Zero-shot Learning.

Hanyao Wang, Yibing Zhan, Liu Liu, Liang Ding, Jun Yu

CoRR, 2024

Healthcare Copilot: Eliciting the Power of General LLMs for Medical Consultation.

Zhiyao Ren, Yibing Zhan, Baosheng Yu, Liang Ding, Dacheng Tao

CoRR, 2024

Mitigating Reward Hacking via Information-Theoretic Reward Modeling.

Yuchun Miao, Sen Zhang, Liang Ding, Rong Bao, Lefei Zhang, Dacheng Tao

CoRR, 2024

Intention Analysis Prompting Makes Large Language Models A Good Jailbreak Defender.

Yuqi Zhang, Liang Ding, Lefei Zhang, Dacheng Tao

CoRR, 2024

POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation.

Shilong Pan, Zhiliang Tian, Liang Ding, Zhen Huang, Zhihua Wen, Dongsheng Li

CoRR, 2024

WisdoM: Improving Multimodal Sentiment Analysis by Fusing Contextual World Knowledge.

Wenbin Wang, Liang Ding, Li Shen, Yong Luo, Han Hu, Dacheng Tao

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Learning from Imperfect Data: Towards Efficient Knowledge Distillation of Autoregressive Language Models for Text-to-SQL.

Qihuang Zhong, Kunfeng Chen, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Self-Powered LLM Modality Expansion for Large Speech-Text Models.

Tengfei Yu, Xuebo Liu, Zhiyi Hou, Liang Ding, Dacheng Tao, Min Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Revisiting Catastrophic Forgetting in Large Language Model Tuning.

Hongyu Li, Liang Ding, Meng Fang, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Context-aware Watermark with Semantic Balanced Green-red Lists for Large Language Models.

Yuxuan Guo, Zhiliang Tian, Yiping Song, Tianlun Liu, Liang Ding, Dongsheng Li

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer.

Boan Liu, Liang Ding, Li Shen, Keqin Peng, Yu Cao, Dazhao Cheng, Dacheng Tao

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Sheared Backpropagation for Fine-Tuning Foundation Models.

Zhiyuan Yu, Li Shen, Liang Ding, Xinmei Tian, Yixin Chen, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Take Care of Your Prompt Bias! Investigating and Mitigating Prompt Bias in Factual Knowledge Extraction.

Ziyang Xu, Keqin Peng, Liang Ding, Dacheng Tao, Xiliang Lu

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset.

Xinyu Ma, Xuebo Liu, Derek F. Wong, Jun Rao, Bei Li, Liang Ding, Lidia S. Chao, Dacheng Tao, Min Zhang

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

ROSE Doesn't Do That: Boosting the Safety of Instruction-Tuned Large Language Models with Reverse Prompt Contrastive Decoding.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Revisiting Knowledge Distillation for Autoregressive Language Models.

Qihuang Zhong, Liang Ding, Li Shen, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Speech Sense Disambiguation: Tackling Homophone Ambiguity in End-to-End Speech Translation.

Tengfei Yu, Xuebo Liu, Liang Ding, Kehai Chen, Dacheng Tao, Min Zhang

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Uncertainty Aware Learning for Language Model Alignment.

Yikun Wang, Rui Zheng, Liang Ding, Qi Zhang, Dahua Lin, Dacheng Tao

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

OOP: Object-Oriented Programming Evaluation Benchmark for Large Language Models.

Shuai Wang, Liang Ding, Li Shen, Yong Luo, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Revisiting Demonstration Selection Strategies in In-Context Learning.

Keqin Peng, Liang Ding, Yancheng Yuan, Xuebo Liu, Min Zhang, Yuanxin Ouyang, Dacheng Tao

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation.

Shilong Pan, Zhiliang Tian, Liang Ding, Haoqi Zheng, Zhen Huang, Zhihua Wen, Dongsheng Li

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models.

Qingyu Lu, Baopu Qiu, Liang Ding, Kanjian Zhang, Tom Kocmi, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

DB-LLM: Accurate Dual-Binarization for Efficient LLMs.

Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Multi-Step Denoising Scheduled Sampling: Towards Alleviating Exposure Bias for Diffusion Models.

Zhiyao Ren, Yibing Zhan, Liang Ding, Gaoang Wang, Chaoyue Wang, Zhongyi Fan, Dacheng Tao

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup.

Yan Sun, Li Shen, Hao Sun, Liang Ding, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

A perioperative risk assessment dataset with multi-view data based on online accelerated pairwise comparison.

Xinyao Li, Yibing Zhan, Yanhua Zhao, Yiqiang Wu, Liang Ding, Yuanyuan Li, Dapeng Tao, Hua Jin

Inf. Fusion, November, 2023

Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-Based Sentiment Analysis.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Hua Jin, Dacheng Tao

IEEE Trans. Knowl. Data Eng., October, 2023

KE-X: Towards subgraph explanations of knowledge graph embedding based on knowledge information gain.

Dong Zhao, Guojia Wan, Yibing Zhan, Zengmao Wang, Liang Ding, Zhigao Zheng, Bo Du

Knowl. Based Syst., October, 2023

Recurrent graph encoder for syntax-aware neural machine translation.

Liang Ding, Longyue Wang, Siyou Liu

Int. J. Mach. Learn. Cybern., April, 2023

Dynamic Contrastive Distillation for Image-Text Retrieval.

Jun Rao, Liang Ding, Shuhan Qi, Meng Fang, Yang Liu, Li Shen, Dacheng Tao

IEEE Trans. Multim., 2023

Unified Instance and Knowledge Alignment Pretraining for Aspect-Based Sentiment Analysis.

Juhua Liu, Qihuang Zhong, Liang Ding, Hua Jin, Bo Du, Dacheng Tao

IEEE ACM Trans. Audio Speech Lang. Process., 2023

Concrete Subspace Learning based Interference Elimination for Multi-task Model Fusion.

Anke Tang, Li Shen, Yong Luo, Liang Ding, Han Hu, Bo Du, Dacheng Tao

CoRR, 2023

SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image Classification.

Lei Wang, Yibing Zhan, Leilei Ma, Dapeng Tao, Liang Ding, Chen Gong

CoRR, 2023

Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation.

Changtong Zan, Liang Ding, Li Shen, Yibin Lei, Yibing Zhan, Weifeng Liu, Dacheng Tao

CoRR, 2023

Deep Model Fusion: A Survey.

Weishi Li, Yong Peng, Miao Zhang, Liang Ding, Han Hu, Li Shen

CoRR, 2023

MerA: Merging Pretrained Adapters For Few-Shot Learning.

Shwai He, Run-Ze Fan, Liang Ding, Li Shen, Tianyi Zhou, Dacheng Tao

CoRR, 2023

Recursively Summarizing Enables Long-Term Dialogue Memory in Large Language Models.

Qingyue Wang, Liang Ding, Yanan Cao, Zhiliang Tian, Shi Wang, Dacheng Tao, Li Guo

CoRR, 2023

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

Fei Wang, Liang Ding, Jun Rao, Ye Liu, Li Shen, Changxing Ding

CoRR, 2023

Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks.

Haoqi Zheng, Qihuang Zhong, Liang Ding, Zhiliang Tian, Xin Niu, Dongsheng Li, Dacheng Tao

CoRR, 2023

On Efficient Training of Large-Scale Deep Learning Models: A Literature Review.

Li Shen, Yan Sun, Zhiyuan Yu, Liang Ding, Xinmei Tian, Dacheng Tao

CoRR, 2023

Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models: A Case Study on ChatGPT.

Qingyu Lu, Baopu Qiu, Liang Ding, Liping Xie, Dacheng Tao

CoRR, 2023

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System.

Chao Xue, Wei Liu, Shuai Xie, Zhenfang Wang, Jiaxing Li, Xuyang Peng, Liang Ding, Shanshan Zhao, Qiong Cao, Yibo Yang, Fengxiang He, Bohua Cai, Rongcheng Bian, Yiyan Zhao, Heliang Zheng, Xiangyang Liu, Dongkai Liu, Daqing Liu, Li Shen, Chang Li, Shijin Zhang, Yukang Zhang, Guanpu Chen, Shixiang Chen, Yibing Zhan, Jing Zhang, Chaoyue Wang, Dacheng Tao

CoRR, 2023

Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

CoRR, 2023

Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE.

Qihuang Zhong, Liang Ding, Keqin Peng, Juhua Liu, Bo Du, Li Shen, Yibing Zhan, Dacheng Tao

CoRR, 2023

SD-Conv: Towards the Parameter-Efficiency of Dynamic Convolution.

Shwai He, Chenbo Jiang, Daize Dong, Liang Ding

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism.

Zheng Zhang, Donglin Yang, Yaqi Xia, Liang Ding, Dacheng Tao, Xiaobo Zhou, Dazhao Cheng

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Prompt-Learning for Cross-Lingual Relation Extraction.

Chiaming Hsu, Changtong Zan, Liang Ding, Longyue Wang, Xiaoting Wang, Weifeng Liu, Fu Lin, Wenbin Hu

Proceedings of the International Joint Conference on Neural Networks, 2023

Gapformer: Graph Transformer with Graph Pooling for Node Classification.

Chuang Liu, Yibing Zhan, Xueqi Ma, Liang Ding, Dapeng Tao, Jia Wu, Wenbin Hu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape.

Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao

Proceedings of the International Conference on Machine Learning, 2023

FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy.

Yan Sun, Li Shen, Tiansheng Huang, Liang Ding, Dacheng Tao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Zero-shot Sharpness-Aware Quantization for Pre-trained Language Models.

Miaoxi Zhu, Qihuang Zhong, Li Shen, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks.

Haoqi Zheng, Qihuang Zhong, Liang Ding, Zhiliang Tian, Xin Niu, Changjian Wang, Dongsheng Li, Dacheng Tao

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

PromptST: Abstract Prompt Learning for End-to-End Speech Translation.

Tengfei Yu, Liang Ding, Xuebo Liu, Kehai Chen, Meishan Zhang, Dacheng Tao, Min Zhang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Making the Most of ChatGPT for Machine Translation.

Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Merging Experts into One: Improving Computational Efficiency of Mixture of Experts.

Shwai He, Run-Ze Fan, Liang Ding, Li Shen, Tianyi Zhou, Dacheng Tao

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Revisiting Token Dropping Strategy in Efficient BERT Pretraining.

Qihuang Zhong, Liang Ding, Juhua Liu, Xuebo Liu, Min Zhang, Bo Du, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Self-Evolution Learning for Discriminative Language Model Pretraining.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Divide, Conquer, and Combine: Mixture of Semantic-Independent Experts for Zero-Shot Dialogue State Tracking.

Qingyue Wang, Liang Ding, Yanan Cao, Yibing Zhan, Zheng Lin, Shi Wang, Dacheng Tao, Li Guo

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Token-Level Self-Evolution Training for Sequence-to-Sequence Learning.

Keqin Peng, Liang Ding, Qihuang Zhong, Yuanxin Ouyang, Wenge Rong, Zhang Xiong, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

Toward Human-Like Evaluation for Natural Language Generation with Error Analysis.

Qingyu Lu, Liang Ding, Liping Xie, Kanjian Zhang, Derek F. Wong, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Unsupervised Dense Retrieval with Relevance-Aware Contrastive Pre-Training.

Yibin Lei, Liang Ding, Yu Cao, Changtong Zan, Andrew Yates, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

PAD-Net: An Efficient Framework for Dynamic Networks.

Shwai He, Liang Ding, Daize Dong, Boan Liu, Fuqiang Yu, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

TransGEC: Improving Grammatical Error Correction with Translationese.

Tao Fang, Xuebo Liu, Derek F. Wong, Runzhe Zhan, Liang Ding, Lidia S. Chao, Dacheng Tao, Min Zhang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

CASN: Class-Aware Score Network for Textual Adversarial Detection.

Rong Bao, Rui Zheng, Liang Ding, Qi Zhang, Dacheng Tao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Improving Simultaneous Machine Translation with Monolingual Data.

Hexuan Deng, Liang Ding, Xuebo Liu, Meishan Zhang, Dacheng Tao, Min Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Original or Translated? On the Use of Parallel Data for Translation Quality Estimation.

Baopu Qiu, Liang Ding, Di Wu, Lin Shang, Yibing Zhan, Dacheng Tao

CoRR, 2022

Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE.

Qihuang Zhong, Liang Ding, Yibing Zhan, Yu Qiao, Yonggang Wen, Li Shen, Juhua Liu, Baosheng Yu, Bo Du, Yixin Chen, Xinbo Gao, Chunyan Miao, Xiaoou Tang, Dacheng Tao

CoRR, 2022

Cherry Hypothesis: Identifying the Cherry on the Cake for Dynamic Networks.

Shwai He, Liang Ding, Daize Dong, Boan Liu, Fuqiang Yu, Dacheng Tao

CoRR, 2022

SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters.

Shwai He, Liang Ding, Daize Dong, Miao Zhang, Dacheng Tao

CoRR, 2022

Vega-MT: The JD Explore Academy Translation System for WMT22.

Changtong Zan, Keqin Peng, Liang Ding, Baopu Qiu, Boan Liu, Shwai He, Qingyu Lu, Zheng Zhang, Chuang Liu, Weifeng Liu, Yibing Zhan, Dacheng Tao

CoRR, 2022

Parameter-Efficient and Student-Friendly Knowledge Distillation.

Jun Rao, Xv Meng, Liang Ding, Shuhan Qi, Dacheng Tao

CoRR, 2022

E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation.

Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao

CoRR, 2022

BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation.

Zheng Zhang, Liang Ding, Dazhao Cheng, Xuebo Liu, Min Zhang, Dacheng Tao

CoRR, 2022

Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation.

Changtong Zan, Liang Ding, Li Shen, Yu Cao, Weifeng Liu, Dacheng Tao

CoRR, 2022

Improving Neural Machine Translation by Denoising Training.

Liang Ding, Keqin Peng, Dacheng Tao

CoRR, 2022

Vega-MT: The JD Explore Academy Machine Translation System for WMT22.

Changtong Zan, Keqin Peng, Liang Ding, Baopu Qiu, Boan Liu, Shwai He, Qingyu Lu, Zheng Zhang, Chuang Liu, Weifeng Liu, Yibing Zhan, Dacheng Tao

Proceedings of the Seventh Conference on Machine Translation, 2022

Where Does the Performance Improvement Come From?: - A Reproducibility Concern about Image-Text Retrieval.

Jun Rao, Fei Wang, Liang Ding, Shuhan Qi, Yibing Zhan, Weifeng Liu, Dacheng Tao

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

MirrorAlign: A Super Lightweight Unsupervised Word Alignment Model via Cross-Lingual Contrastive Learning.

Di Wu, Liang Ding, Shuo Yang, Mingyang Li

Proceedings of the 19th International Conference on Spoken Language Translation, 2022

Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models.

Qihuang Zhong, Liang Ding, Li Shen, Peng Mi, Juhua Liu, Bo Du, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters.

Shwai He, Liang Ding, Daize Dong, Jeremy Zhang, Dacheng Tao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning.

Lin Zhang, Li Shen, Liang Ding, Dacheng Tao, Ling-Yu Duan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation.

Changtong Zan, Liang Ding, Li Shen, Yu Cao, Weifeng Liu, Dacheng Tao

Proceedings of the 29th International Conference on Computational Linguistics, 2022

A Contrastive Cross-Channel Data Augmentation Framework for Aspect-Based Sentiment Analysis.

Bing Wang, Liang Ding, Qihuang Zhong, Ximing Li, Dacheng Tao

Proceedings of the 29th International Conference on Computational Linguistics, 2022

Redistributing Low-Frequency Words: Making the Most of Monolingual Data in Non-Autoregressive Translation.

Liang Ding, Longyue Wang, Shuming Shi, Dacheng Tao, Zhaopeng Tu

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

The USYD-JD Speech Translation System for IWSLT 2021.

Liang Ding, Di Wu, Dacheng Tao

CoRR, 2021

Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding.

Di Wu, Yiren Chen, Liang Ding, Dacheng Tao

CoRR, 2021

SLUA: A Super Lightweight Unsupervised Word Alignment Model via Cross-Lingual Contrastive Learning.

Di Wu, Liang Ding, Shuo Yang, Dacheng Tao

CoRR, 2021

The USYD-JD Speech Translation System for IWSLT2021.

Liang Ding, Dacheng Tao

Proceedings of the 18th International Conference on Spoken Language Translation, 2021

Understanding and Improving Lexical Choice in Non-Autoregressive Translation.

Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu

Proceedings of the 9th International Conference on Learning Representations, 2021

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning.

Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Zhaopeng Tu

Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Efficiently Diversifying Dialogue Generation Via Embedding Augmentation.

Yu Cao, Liang Ding, Zhiliang Tian, Meng Fang

Proceedings of the IEEE International Conference on Acoustics, 2021

Improving Neural Machine Translation by Bidirectional Training.

Liang Ding, Di Wu, Dacheng Tao

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation.

Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Shuming Shi, Zhaopeng Tu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

On the Copying Behaviors of Pre-Training for Neural Machine Translation.

Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao, Shuming Shi, Zhaopeng Tu

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Progressive Multi-Granularity Training for Non-Autoregressive Translation.

Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Rejuvenating Low-Frequency Words: Making the Most of Parallel Data in Non-Autoregressive Translation.

Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Tencent AI Lab Machine Translation Systems for WMT20 Chat Translation Task.

Longyue Wang, Zhaopeng Tu, Xing Wang, Li Ding, Liang Ding, Shuming Shi

Proceedings of the Fifth Conference on Machine Translation, 2020

Context-Aware Cross-Attention for Non-Autoregressive Translation.

Liang Ding, Longyue Wang, Di Wu, Dacheng Tao, Zhaopeng Tu

Proceedings of the 28th International Conference on Computational Linguistics, 2020

Self-Attention with Cross-Lingual Position Representation.

Liang Ding, Longyue Wang, Dacheng Tao

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Recurrent Graph Syntax Encoder for Neural Machine Translation.

Liang Ding, Dacheng Tao

CoRR, 2019

The University of Sydney's Machine Translation System for WMT19.

Liang Ding, Dacheng Tao

Proceedings of the Fourth Conference on Machine Translation, 2019