Fangyu Liu
Orcid: 0000-0001-7038-3623Affiliations:
- University of Cambridge, Language Technology Lab, UK
- University of Waterloo, ON, Canada
- Beijing Normal University, Faculty of Geographical Science, China
According to our database1,
Fangyu Liu
authored at least 55 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
-
on fangyuliu.me
On csauthors.net:
Bibliography
2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
Trans. Assoc. Comput. Linguistics, 2023
Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models.
CoRR, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023
Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
CoRR, 2022
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022
Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022
How to tackle an emerging topic? Combining strong and weak labels for Covid news NER.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022
Proceedings of the International Conference on Machine Learning, 2022
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
2021
Fast, Effective and Self-Supervised: Transforming Masked LanguageModels into Universal Lexical and Sentence Encoders.
CoRR, 2021
DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models.
Proceedings of the 25th Conference on Computational Natural Language Learning, 2021
Proceedings of the Seventh Workshop on Noisy User-generated Text, 2021
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
ACM Trans. Multim. Comput. Commun. Appl., 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Proceedings of the Advances in Artificial Intelligence, 2019
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019
2018
Joint Discriminative Dictionary and Classifier Learning for ALS Point Cloud Classification.
IEEE Trans. Geosci. Remote. Sens., 2018
Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model.
CoRR, 2018
CoRR, 2018
Auto-classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model.
Proceedings of the Computer Vision - ACCV 2018 Workshops, 2018
2017
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-Scale 3D Point Clouds.
Proceedings of the IEEE International Conference on Computer Vision, 2017