Laleh Seyyed-Kalantari

Orcid: 0000-0002-1059-7125

According to our database1, Laleh Seyyed-Kalantari authored at least 24 papers between 2009 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Template-Based Probes Are Imperfect Lenses for Counterfactual Bias Evaluation in LLMs.
Trans. Mach. Learn. Res., 2026

Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
Algorithms Trained on Normal Chest X-rays Can Predict Health Insurance Types.
CoRR, November, 2025

Simulating Social Behavior of LLM-Based Autonomous Negotiator Agents in a Game-Theoretical Framework Using Multi-Agent Systems.
Int. J. Hum. Comput. Interact., 2025

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.
Artif. Intell. Medicine, 2025

MLHOps: Machine Learning Health Operations.
IEEE Access, 2025

Underdiagnosis Bias Mitigation With Expert Foundation Model's Representation.
IEEE Access, 2025

Representation Is All We Need: Performance and Fairness of Google X-ray Foundation Model Representations - A Preliminary Study.
Proceedings of the 13th IEEE International Conference on Healthcare Informatics, 2025

ZFusion: Efficient Deep Compositional Zero-Shot Learning for Blind Image Super-Resolution with Generative Diffusion Prior.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

We Politely Insist: Your LLM Must Learn the Persian Art of Taarof.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Dialectic Preference Bias in Large Language Models.
Proceedings of the 2025 AAAI Spring Symposium Series, 2025

2024
The Impact of Unstated Norms in Bias Analysis of Language Models.
CoRR, 2024

Localisation of Racial Information in Chest X-Ray for Deep Learning Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors.
CoRR, 2023

Towards Trustworthy Artificial Intelligence for Equitable Global Health.
CoRR, 2023

Soft-prompt Tuning for Large Language Models to Evaluate Bias.
CoRR, 2023

Performance Gaps of Artificial Intelligence Models Screening Mammography - Towards Fair and Interpretable Models.
CoRR, 2023

MLHOps: Machine Learning for Healthcare Operations.
CoRR, 2023

Evaluating Knowledge Transfer in the Neural Network for Medical Images.
IEEE Access, 2023

2021
Reading Race: AI Recognises Patient's Racial Identity In Medical Images.
CoRR, 2021

CheXclusion: Fairness gaps in deep chest X-ray classifiers.
Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021

An empirical framework for domain generalization in clinical settings.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers.
CoRR, 2020

2009
Detection, Identification and Tracking of Flying Objects in Three Dimensions Using Multistatic Radars.
Int. J. Commun. Netw. Syst. Sci., 2009


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