3 citations · 7 across the 9 of their papers we have counts for
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cs.LG2025
Adaptive Federated Learning Defences via Trust-Aware Deep Q-Networks
Vedant Palit
Federated learning is vulnerable to poisoning and backdoor attacks under partial observability. We formulate defence as a partially observable sequential decision problem and intro…
cs.CV2025★ 2 cited
Forgotten Polygons: Multimodal Large Language Models are Shape-Blind
William Rudman, Michal Golovanevsky, Amir Bar +4
Despite strong performance on vision-language tasks, Multimodal Large Language Models (MLLMs) struggle with mathematical problem-solving, with both open-source and state-of-the-art…
cs.CL2025★ 3 cited
Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case
Kaushik Roy, Harshul Surana, Darssan Eswaramoorthi +4
Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic assessments, which could alleviate th…