Number of items: 28.
2024
Arslan Manzoor, M., AlBarri, S., Xian, Z., Meng, Z. , Nakov, P. and Liang, S.
(2024)
Multimodality representation learning: a survey on evolution, pretraining and its applications.
ACM Transactions on Multimedia Computing, Communications, and Applications, 20(3),
74.
(doi: 10.1145/3617833)
Tang, S., Meng, Z. and Liang, S.
(2024)
Dynamic co-embedding model for temporal attributed networks.
IEEE Transactions on Neural Networks and Learning Systems, 35(3),
pp. 3488-3502.
(doi: 10.1109/TNNLS.2022.3193564)
(PMID:35900994)
Fang, J., Meng, Z. and Macdonald, C.
(2024)
Enhancing Late Interaction with Informative Entities for Passage Retrieval.
46th European Conference on Information Retrieval (ECIR 2024): The First Knowledge-Enhanced Information Retrieval Workshop (KEIR@ECIR 2024), Glasgow, Scotland, 24-28 March 2024.
(Accepted for Publication)
Chen, G., Li, X., Meng, Z. , Liang, S. and Bing, L.
(2024)
CLEX: Continuous Length Extrapolation for Large Language Models.
In: 12th International Conference on Learning Representations, Vienna, Austria, 7-11 May 2024,
(Accepted for Publication)
Cao, J., Fang, J., Meng, Z. and Liang, S.
(2024)
Knowledge graph embedding: a survey from the perspective of representation spaces.
ACM Computing Surveys,
(doi: 10.1145/3643806)
(Early Online Publication)
Chen, X., Wang, Y., Fang, J., Meng, Z. and Liang, S.
(2024)
Heterogeneous graph contrastive learning with metapath-based augmentations.
IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1),
pp. 1003-1014.
(doi: 10.1109/TETCI.2023.3322341)
Long, Z. , McCreadie, R. , Aragon Camarasa, G. and Meng, Z.
(2024)
LACVIT: A Label-aware Contrastive Fine-tuning Framework for Vision Transformers.
In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, 14-19 Apr 2024,
(Accepted for Publication)
2023
Fu, Z., Zhang, M., Meng, Z. , Shen, Y., Buckeridge, D. and Collier, N.
(2023)
BAND: Biomedical Alert News Dataset.
In: 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, 20-27 February 2024,
(Accepted for Publication)
Cao, P., Wang, Y., Zhang, Q. and Meng, Z.
(2023)
GenKIE: Robust Generative Multimodal Document Key Information Extraction.
In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023,
pp. 14702-14713.
(doi: 10.18653/v1/2023.findings-emnlp.979)
Fu, Z., Su, Y., Meng, Z. and Collier, N.
(2023)
Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization.
In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023,
pp. 14621-14635.
(doi: 10.18653/v1/2023.emnlp-main.903)
Fang, J., Meng, Z. and Macdonald, C.
(2023)
KGPR: Knowledge Graph Enhanced Passage Ranking.
In: 32nd ACM International Conference on Information and Knowledge Management, Birmingham, UK, 21-25 Oct 2023,
pp. 3880-3885.
ISBN 9798400701245
(doi: 10.1145/3583780.3615252)
Wu, B., Meng, Z. and Liang, S.
(2023)
Dynamic Bayesian contrastive predictive coding model for personalized product search.
ACM Transactions on the Web,
(doi: 10.1145/3609225)
(Early Online Publication)
Fang, J., Wang, X., Meng, Z. , Xie, P., Huang, F. and Jiang, Y.
(2023)
MANNER: A Variational Memory-Augmented Model for Cross Domain Few-Shot Named Entity Recognition.
In: 61st Annual Meeting of the Association for Computational Linguistics (ACL '23), Toronto, Canada, 9-14 July 2023,
(doi: 10.18653/v1/2023.acl-long.234)
Liu, S., Meng, Z. , Macdonald, C. and Ounis, I.
(2023)
Graph neural pre-training for recommendation with side information.
ACM Transactions on Information Systems, 41(3),
74.
(doi: 10.1145/3568953)
Yuan, Z., Hu, S., Vulic, I., Korhonen, A. and Meng, Z.
(2023)
Can Pretrained Language Models (Yet) Reason Deductively?
In: 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), Dubrovnik, Croatia, 2-6 May 2023,
pp. 1447-1462.
(doi: 10.18653/v1/2023.eacl-main.106)
Wang, Y., Chen, X., Fang, J., Meng, Z. and Liang, S.
(2023)
Enhancing conversational recommendation systems with representation fusion.
ACM Transactions on the Web, 17(1),
6.
(doi: 10.1145/3577034)
Chen, G., Liu, F., Meng, Z. and Liang, S.
(2023)
Revisiting Parameter-Efficient Tuning: Are We Really There Yet?
In: 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi, 7-11 Dec 2022,
pp. 2612-2626.
2022
Meng, Z. et al.
(2022)
BioCaster in 2021: automatic disease outbreaks detection from global news media.
Bioinformatics, 38(18),
pp. 4446-4448.
(doi: 10.1093/bioinformatics/btac497)
(PMID:35900173)
(PMCID:PMC9477518)
Meng, Z. , Liu, F., Shareghi, E., Su, Y., Collins, C. and Collier, N.
(2022)
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models.
In: 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Dublin, Ireland, 22-27 May 2022,
pp. 4798-4810.
Wang, Y., Xin, X., Meng, Z. , Jose, J. M. , Feng, F. and He, X.
(2022)
Learning Robust Recommenders Through Cross-Model Agreement.
In: ACM Web Conference 2022, Lyon, France, 25-29 April 2022,
pp. 2015-2025.
ISBN 9781450390965
(doi: 10.1145/3485447.3512202)
Liang, S., Luo, Y. and Meng, Z.
(2022)
Profiling users for question answering communities via flow-based constrained co-embedding model.
ACM Transactions on Information Systems, 40(2),
34.
(doi: 10.1145/3470565)
2021
Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I.
(2021)
Variational Bayesian representation learning for grocery recommendation.
Information Retrieval, 24(4-5),
pp. 347-369.
(doi: 10.1007/s10791-021-09397-1)
2020
Meng, Z. , Mccreadie, R. , Macdonald, C. and Ounis, I.
(2020)
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models.
In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020,
pp. 681-686.
ISBN 9781450375832
(doi: 10.1145/3383313.3418479)
Meng, Z. et al.
(2020)
BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems.
In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020,
pp. 588-590.
ISBN 9781450375832
(doi: 10.1145/3383313.3411524)
Huang, H., Meng, Z. and Liang, S.
(2020)
Recurrent neural variational model for follower-based influence maximization.
Information Sciences, 528,
pp. 280-293.
(doi: 10.1016/j.ins.2020.04.023)
Liu, S., Ounis, I. , Macdonald, C. and Meng, Z.
(2020)
A Heterogeneous Graph Neural Model for Cold-Start Recommendation.
In: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China, 25-30 Jul 2020,
pp. 2029-2032.
ISBN 9781450380164
(doi: 10.1145/3397271.3401252)
2019
Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I.
(2019)
Variational Bayesian Context-aware Representation for Grocery Recommendation.
In: 13th ACM Conference on Recommender Systems (RecSys19) - CARS 2019 Workshop, Copenhagen, Denmark, 16-20 Sept 2019,
Meng, Z. , Liang, S., Fang, J. and Xiao, T.
(2019)
Semi-supervisedly Co-embedding Attributed Networks.
In: Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 08-14 Dec 2019,
This list was generated on Thu May 2 22:36:54 2024 BST.