Shang, Lifeng

TinyBERT: Distilling BERT for natural language understanding

Jiao, X., Yin, Y., Shang, L., Jiang, X., Chen, X., Li, L., Wang, F., & Liu, Q. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Topic ModelingAdvanced Neural Network Applications

Cited by 1,786

Multimodal Convolutional Neural Networks for Matching Image and Sentence

Ma, L., Lu, Z., Shang, L., & Li, H. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 334

Neural Generative Question Answering

Yin, J., Jiang, X., Lu, Z., Shang, L., Li, H., & Li, X. (2016) · Proceedings of the Workshop on Human-Computer Question Answering

Topic ModelingNatural Language Processing Techniques

Cited by 186

TernaryBERT: Distillation-aware Ultra-low Bit BERT

Zhang, W., Hou, L., Yin, Y., Shang, L., Chen, X., Jiang, X., & Liu, Q. (2020) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 150

DynaBERT: Dynamic BERT with Adaptive Width and Depth

Hou, L., Huang, Z., Shang, L., Jiang, X., Chen, X., & Liu, Q. (2020) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 143

Generate & Rank: A Multi-task Framework for Math Word Problems

Shen, J., Yin, Y., Li, L., Shang, L., Jiang, X., Zhang, M., & Liu, Q. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021

Topic ModelingMathematics, Computing, and Information Processing

Cited by 88

Aligning Large Language Models with Human: A Survey

Wang, Y., Zhong, W., Li, L., Mi, F., Zeng, X., Huang, W., Shang, L., Jiang, X., & Liu, Q. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 69

FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models

Jiang, Y., Wang, Y., Zeng, X., Zhong, W., Li, L., Mi, F., Shang, L., Jiang, X., Liu, Q., & Wang, W. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 55

BinaryBERT: Pushing the Limit of BERT Quantization

Bai, H., Zhang, W., Hou, L., Shang, L., Jin, J., Jiang, X., Liu, Q., Lyu, M., & King, I. (2020) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 42

Read before Generate! Faithful Long Form Question Answering with Machine Reading

Su, D., Li, X., Zhang, J., Shang, L., Jiang, X., Liu, Q., & Fung, P. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 37

Read before Generate! Faithful Long Form Question Answering with Machine Reading

Su, D., Li, X., Zhang, J., Shang, L., Jiang, X., Liu, Q., & Fung, P. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Topic ModelingInformation Retrieval and Search Behavior

Cited by 37

AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models

Yin, Y., Chen, C., Shang, L., Jiang, X., Chen, X., & Liu, Q. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Topic ModelingMachine Learning and Data Classification

Cited by 24

Learning to edit: Aligning llms with knowledge editing

Jiang, Y., Wang, Y., Wu, C., Zhong, W., Zeng, X., Gao, J., Li, L., Jiang, X., Shang, L., Tang, R., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 12