Evaluation Bias and Epistemic Inequality in Global Software Development, Sam Khosravi and Amir H. Payberah, arXiv:2607.12563, July 2026 [pdf]
StarDTox: Is Fairness in Language Models Just a Few Prompts Away?, Shirin Tahmasebi, Narjes Nikzad, Amir H. Payberah, Meysam Asgari-chenaghlu, and Mihhail Matskin, Workshop on Advances in Artificial Intelligence and Machine Learning (AIML), co-located with IEEE COMPSAC, Madrid, Spain, July 2026 [pdf]
Technocolonialism and the Politics of Digital Humanitarianism, Amir H. Payberah, Dialogues on Digital Society, May 2026 [pdf]
PBBQ: A Persian Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models, Farhan Farsi, Shayan Bali, Fatemeh Valeh, Parsa Ghofrani, Alireza Pakniat, Kian Kashfipour, and Amir H. Payberah, Language Resources and Evaluation Conference (LREC), May 2026 [pdf]
The Value of Visualization Literacy, Derya Akbaba, Data Literacy Workshop, co-located with CHI, Barcelona, Spain, April 2026 [pdf]
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]
AquaCluster: Using Satellite Images And Self-supervised Machine Learning Networks To Detect Water Hidden Under Vegetation, Ioannis Iakovidisa, Zahra Kalantaria, Amir H. Payberah, Fernando Jaramillo, and Francisco J. Peña, arXiv:2506.08214 , 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]
DeepAqua: Semantic Segmentation of Wetland Water Surfaces With SAR Imagery Using Deep Neural Networks Without Manually Annotated Data, Francisco J. Peña, Clara Hübinger, Amir H. Payberah, and Fernando Jaramillo, Elsevier International Journal of Applied Earth Observation and Geoinformation, 2024 [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]