IntersectionRE: Mitigating Intersectional Bias in Relation Extraction Through Coverage-Driven Augmentation, Amirhossein Layegh, Amir H. Payberah, and Mihhail Matskin, Identity-Aware AI Workshop, co-located with ECAI, Bologna, Italy, October 2025 [pdf]
PureBiasoMeter: Decoupling Popularity Bias from User Fairness in LLM-Based Recommender Systems. Shirin Tahmasebi, Muhammad Hamad, Amir H. Payberah, and Mihhail Matskin, Workshop on Recommender Systems for Sustainability and Social Good (RecSoGood), co-located with ACM RecSys, Prague, Czech Republic, September 2025 [pdf]
Who Gets the Mic? Investigating Gender Bias in the Speaker Assignment of a Speech-LLM, Dariia Puhach, Amir H. Payberah, and Éva Székely, Interspeech Conference, Rotterdam, The Netherlands, August 2025 [pdf]
Fact vs. Fiction: Are the Reportedly "Magical" LLM-Based Recommenders Reproducible?, Shirin Tahmasebi, Narjes Nikzad, Amir H. Payberah, Meysam Asgari-Chenaghlu and Mihhail Matskin, European Conference on Information Retrieval (ECIR), Tuscany, Italy, April 2025 [pdf]
REA: Refine-Estimate-Answer Prompting for Zero-Shot Relation Extraction, Amirhossein Layegh, Amir H. Payberah, and Mihhail Matskin, International Conference on Natural Language and Information Systems (NLDB), Turin, Italy, June 2024 [pdf]
Wiki-based Prompts for Enhancing Relation Extraction using Language Models, Amirhossein Layegh, Amir H. Payberah, Ahmet Soylu, Dumitru Roman, and Mihhail Matskin, ACM/SIGAPP Symposium On Applied Computing (SAC), Avila, Spain, April 2024 [pdf]
ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER, Amirhossein Layegh, Amir H. Payberah, Ahmet Soylu, Dumitru Roman, and Mihhail Matskin, COMPSAC Symposium on Autonomous Systems (ASYS), Torino, Italy, June 2023 [pdf]
Node Context Selection in Transformer-Based Graph Representation Learning Models, Tianze Wang, Amir H. Payberah, and Vladimir Vlassov, Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs), co-located with IEEE BigData, Osaka, Japan, December 2022 [pdf]