@inproceedings{hoang2025srs,title={Don't Get Ahead of Yourself: A Critical Study on Data Leakage in Offline Evaluation of Sequential Recommenders},author={Huy, Hoang Le and Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 19th ACM Conference on Recommender Systems},year={2025},note={to be present.},}
@inproceedings{kaiyue2025si,title={Disentangling User and Item Sequence Patterns in Sequential Recommendation Data Sets},author={Liu, Kaiyue and Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 19th ACM Conference on Recommender Systems},year={2025},note={to be present.},}
@inproceedings{liu2024GAN,title={Sample, Nudge and Rank: Exploiting Interpretable GAN Controls for Exploratory Search},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 28th International Conference on Intelligent User Interfaces},pages={582-596},year={2024},}
@inproceedings{denis2024crossdomain,title={On the Negative Perception of Cross-domain Recommendations and Explanations},author={Kotkov, Denis and Medlar, Alan and Liu, Yang and G{\l}owacka, Dorota},booktitle={Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},year={2024},pages={2102--2113},}
@inproceedings{liu2023irt,title={What We Evaluate When We Evaluate Recommender Systems: Understanding Recommender Systems’ Performance using Item Response Theory},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 17th ACM conference on recommender systems},pages={658–-670},numpages={13},year={2023},}
@inproceedings{liu2023consistency,title={On the consistency, discriminative power and robustness of sampled metrics in offline top-n recommender system evaluation},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 17th ACM Conference on Recommender Systems},pages={1152--1157},year={2023},}
2022
UMAP
Critiquing-based Modeling of Subjective Preferences
Alan Medlar, Jing Li, Yang Liu, and Dorota Głowacka
In Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, 2022
@inproceedings{medlar2022critiquing,title={Critiquing-based Modeling of Subjective Preferences},author={Medlar, Alan and Li, Jing and Liu, Yang and G{\l}owacka, Dorota},booktitle={Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization},pages={234--242},year={2022},}
@article{liu2022lexical,title={Lexical ambiguity detection in professional discourse},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},journal={Information Processing \& Management},volume={59},number={5},pages={103000},year={2022},publisher={Elsevier},}
@inproceedings{liu2022rogue,title={ROGUE: A System for Exploratory Search of GANs},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},pages={3278--3282},year={2022},}
2021
ICTIR
Can Language Models Identify Wikipedia Articles with Readability and Style Issues?
Yang Liu, Alan Medlar, and Dorota Głowacka
In Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval, 2021
@inproceedings{liu2021can,title={Can Language Models Identify Wikipedia Articles with Readability and Style Issues?},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval},pages={113--117},year={2021},}
Eval4NLP
Statistically Significant Detection of Semantic Shifts using Contextual Word Embeddings
Yang Liu, Alan Medlar, and Dorota Głowacka
In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems, 2021
@inproceedings{liu2021statistically,title={{Statistically Significant Detection of Semantic Shifts using Contextual Word Embeddings}},author={Liu, Yang and Medlar, Alan and G{\l}owacka, Dorota},booktitle={Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems},year={2021},}