12 papers
HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation
Shaina Raza, Aravind Narayanan, Vahid Reza Khazaie +6
Although recent large multimodal models (LMMs) show impressive progress on vision language tasks, their alignment with human centered (HC) principles such as fairness, ethics, incl…
Learning to Share: Selective Memory for Efficient Parallel Agentic Systems
Joseph Fioresi, Parth Parag Kulkarni, Ashmal Vayani +2
Agentic systems solve complex tasks by coordinating multiple agents that iteratively reason, invoke tools, and exchange intermediate results. To improve robustness and solution qua…
Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future
Shaina Raza, Rizwan Qureshi, Anam Zahid +14
Generative AI is rapidly moving from research to deployment, elevating the need for responsible development, evaluation, and governance. We conduct a PRISMA guided review of 232 st…
MedRoute: RL-Based Dynamic Specialist Routing in Multi-Agent Medical Diagnosis
Ashmal Vayani, Parth Parag Kulkarni, Joseph Fioresi +2
Medical diagnosis using Large Multimodal Models (LMMs) has gained increasing attention due to capability of these models in providing precise diagnoses. These models generally comb…
Beyond Content: How Grammatical Gender Shapes Visual Representation in Text-to-Image Models
Muhammed Saeed, Shaina Raza, Ashmal Vayani +3
Research on bias in Text-to-Image (T2I) models has primarily focused on demographic representation and stereotypical attributes, overlooking a fundamental question: how does gramma…
BBQ-V: Benchmarking Visual Stereotype Bias in Large Multimodal Models
Vishal Narnaware, Ashmal Vayani, Rohit Gupta +2
Stereotype biases in Large Multimodal Models (LMMs) perpetuate harmful societal prejudices, undermining the fairness and equity of AI applications. As LMMs grow increasingly influe…