Position: LLMs Must Use Functor-Based and RAG-Driven Bias Mitigation for Fairness. - Ravi Ranjan; Utkarsh Grover; Agorista Polyzou (CoRR, 2026)

RAZOR: Ratio-Aware Layer Editing for Targeted Unlearning in Vision Transformers and Diffusion Models. - Ravi Ranjan; Utkarsh Grover; Xiaomin Lin 002; Agoritsa Polyzou (CoRR, 2026)

Embodied Foundation Models at the Edge: A Survey of Deployment Constraints and Mitigation Strategies. - Utkarsh Grover; Ravi Ranjan; Mingyang Mao; Trung Tien Dong; Satvik Praveen; Zhenqi Wu; J. Morris Chang; Tinoosh Mohsenin; Yi Sheng; Agoritsa Polyzou; Eiman Kanjo; Xiaomin Lin 002 (CoRR, 2026)

CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs. - Ravi Ranjan; Utkarsh Grover; Mayur Akewar; Xiaomin Lin 002; Agoritsa Polyzou (CoRR, 2026)

G-Drift MIA: Membership Inference via Gradient-Induced Feature Drift in LLMs. - Ravi Ranjan; Utkarsh Grover; Xiaomin Lin 002; Agoritsa Polyzou (CoRR, 2026)

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs. - Ravi Ranjan; Utkarsh Grover; Xiaomin Lin 002; Agoritsa Polyzou (CoRR, 2026)

FAM-Bench: A Multimodal Benchmark for Condition-Aware Food-as-Medicine Reasoning. - Mingyang Mao; Bhargav Rishi Medisetti; Utkarsh Grover; Tanvir Ibrahim; Wenyan Li; Tingting Zhang; Xiaomin Lin 002 (CoRR, 2026)