Conference Proceedings

Erdös Number: 4 (Erdös > Noga Alon > Rudolf Fleischer > Jiong Guo > Yash Raj Shrestha)

  • Feng, Y., Feuerriegel, S., & Shrestha, Y. R. (2026). Contextualizing Recommendation Explanations with LLMs: A User Study. International AAAI Conference on Web and Social Media (ICWSM). paper
  • Bashardoust, A., Feng, Y., Geissler, D., Feuerriegel, S., & Shrestha, Y. R. (2026). The Effect of Education in Prompt Engineering: Evidence from Journalists. International AAAI Conference on Web and Social Media (ICWSM). paper
  • Tataroğlu Özbulak, G. A, Shrestha, Y. R., & Calbimonte, J. P. (2025). CAST-GNN: Continual adaptive learning for custom spatio-temporal knowledge graphs via graph neural networks. Proceedings of the IEEE International Conference on Data Mining (ICDM 2025). IEEE. video
  • Feng, Y., Choudhary, V., & Shrestha, Y. R. (2025). Noise, Adaptation, and Strategy: Assessing LLM Fidelity in Decision-Making. Conference on Empirical Methods in Natural Language Processing (EMNLP). paper
  • Tataroğlu Özbulak, G. A., Shrestha, Y. R., & Calbimonte, J.-P. (2025). STKGNN: Scalable Spatio-Temporal Knowledge Graph Reasoning for Activity Recognition. Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM). paper
  • Koju, S., Bastola, S., Shrestha, P., Amgain, S., Shrestha, Y. R., Poudel, R. P., & Bhattarai, B. (2025). Surgical Vision World Model. MICCAI paper
  • Pokhrel, Sandesh, Sanjay Bhandari, Sharib Ali, Tryphon Lambrou, Anh Nguyen, Yash Raj Shrestha, Angus Watson, Danail Stoyanov, Prashnna Gyawali, and Binod Bhattarai. (2025) NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision. MIUA paper
  • Khanal, B., Pokhrel, S., Bhandari, S., Rana, R., Shrestha, N., Gurung, R.B., Linte, C.A., Watson, A.J., Shrestha, Y.R. and Bhattarai, B., (2025). Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models. MICCAI paper
  • Pokhrel, S., Bhandari, S., Vasquez, E., Shrestha, YR & Bhattarai, B. (2024). Cross-task Data Augmentation by Pseudo-label Generation for Region-based Coronary Artery Instance Segmentation. In MICCAI Workshop on Data Engineering in Medical Imaging (pp. 166-175). Cham: Springer Nature Switzerland. paper
  • Jamet, H., Manderlier, M., Shrestha, Y. R. and Vlachos, M. (2024). Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning. In Proceedings of the 18th ACM Conference on Recommender Systems (pp. 987-992). paper
  • Poudel, P., Shrestha, P., Amgain, S., Shrestha, Y. R., Gyawali, P. & Bhattarai B. (2024). CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 102-112). Cham: Springer Nature Switzerland. paper
  • Bashardoust, A., Feuerriegel, S., & Shrestha, Y. R. (2024). Comparing the willingness to share for human-generated vs. AI-generated fake news. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW2): 1-21. paper
  • Jamet H, Shrestha YR, Vlachos M (2024). Difficulty Estimation and Simplification of French Texts Using LLMs. In International Conference on Intelligent Tutoring Systems (pp. 395-404). Cham: Springer Nature Switzerland. paper
  • Bashardoust, A., Negin, S., Haki, K., & Shrestha, Y. R. (2023) Employing Machine Learning to Advance Agent-based Modeling in Information Systems Research (ICIS) International Conference on Information Systems. paper
  • Herath, S., Jóhannsson, J. G., Shrestha, Y. R., & von Krogh, G. F. (2023). Artificial Intelligence-​​​Augmented Decision Making in Supply Chain Monitoring: An Action Design Research Study. Presented at the European Conference on Information Systems (ECIS 2023), Kristiansand, Norway, June 2023. paper
  • Keidar, D., Zhong, M., Zhang, C., Shrestha, Y. R., & Paudel, B. (2021). Towards Automatic Bias Detection in Knowledge Graphs. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021). Nov 7–11, 2021 paper video
  • Arduini, M., Noci, L., Pirovano, F., Zhang, C., Shrestha, Y. R., & Paudel, B. (2020). Adversarial learning for debiasing knowledge graph embeddings. In MLG 2020: 16th International Workshop on Miningand Learning with Graphs – A Workshop at the KDD Conference, August 24,2020, San Diego, CA.ACM, New York, NY, USA, 7 pages paper video
  • Leopold F., Shrestha, Y. R. & Paudel, B. (2020). A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records. In BioKDD 2020: 19th International Workshop on Data Mining in Bioinformatics, August 24, 2020, San Diego, CA.ACM, New York, NY, USA paper video
  • Shrestha, Y. R., & Yang, Y. (2019). Fairness in Algorithmic Decision-Making: Applications in Multi-Winner Voting, Machine Learning, and Recommender Systems. Algorithms, 12(9), 199. paper
  • Yang, Y., Shrestha, Y. R., & Guo, J. (2016). How Hard Is Bribery with Distance Restrictions? In Proceedings of European Conference on Artificial Intelligence, 363-371 paper
  • Yang, Y., Shrestha, Y. R., Li, W., & Guo, J. (2016). Kernelization of two path searching problems on split graphs. In Frontiers in Algorithmics , Lecture Notes in Computer Science, 238-249. paper
  • Mnich, M., Shrestha, Y. R., & Yang, Y. (2015). When does Schwartz conjecture hold? In Proceedings of the International Joint Conference on Artificial Intelligence, 603-609 paper
  • Guo, J., Shrestha, Y. R., & Yang, Y. (2015). How Credible is the Prediction of a Party-Based Election? In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 1431-1439. International Foundation for Autonomous Agents and Multiagent Systems. paper
  • Yang, Y., Shrestha, Y. R., & Guo, J. (2015). How Hard is Bribery in Party Based Elections?. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems,1725-1726. International Foundation for Autonomous Agents and Multiagent Systems. paper
  • Guo, J., Shrestha, Y. R. (2014). Controlling Two-stage Voting Rules, In Proceedings of European Conference on Artificial Intelligence, Frontiers of Artificial Intelligence and Applications, 263, 411-416 paper
  • Guo, J., & Shrestha, Y. R. (2014) Parameterized Complexity of Edge Interdiction Problems. In: Computing and Combinatorics, Lecture Notes in Computer Science, vol. 8591, 166-178 paper
  • Guo, J., & Shrestha, Y. R. (2014). Complexity of Disjoint Π-Vertex Deletion for Disconnected Forbidden Subgraphs. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 8344, 286-297 paper
  • Guo, J., & Shrestha, Y. R. (2012). Kernelization and Parameterized Complexity of Star Editing and Union Editing. In Algorithms and Computation, Lecture Notes in Computer Science, vol. 7676, 126-135 paper