collaborators

10 papers

cs.CY2026

LLM Harms: A Taxonomy and Discussion

Kevin Chen, Saleh Afroogh, Abhejay Murali +3

This study addresses categories of harm surrounding Large Language Models (LLMs) in the field of artificial intelligence. It addresses five categories of harms addressed before, du…

cs.CY2026

Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions

Junfeng Jiao, Saleh Afroogh, Kevin Chen +3

As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical impera…

cs.CY2026

LLMs and Childhood Safety: Identifying Risks and Proposing a Protection Framework for Safe Child-LLM Interaction

Junfeng Jiao, Saleh Afroogh, Kevin Chen +3

Large Language Models (LLMs) are increasingly embedded in child-facing contexts such as education, companionship, creative tools, but their deployment raises safety, privacy, devel…

cs.CY2026

Generative AI and LLMs in Industry: A text-mining Analysis and Critical Evaluation of Guidelines and Policy Statements Across Fourteen Industrial Sectors

Junfeng Jiao, Saleh Afroogh, Kevin Chen +2

The rise of Generative AI (GAI) and Large Language Models (LLMs) has transformed industrial landscapes, offering unprecedented opportunities for efficiency and innovation while rai…

cs.CR2026

AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows

Ivoline C. Ngong, Keerthiram Murugesan, Swanand Kadhe +3

Agentic systems are increasingly acting on users' behalf, accessing calendars, email, and personal files to complete everyday tasks. Privacy evaluation for these systems has focuse…

cs.CY2026

Evaluating LLM Safety Across Child Development Stages: A Simulated Agent Approach

Abhejay Murali, Saleh Afroogh, Kevin Chen +3

Current safety alignment for Large Language Models (LLMs) implicitly optimizes for a "modal adult user," leaving models vulnerable to distributional shifts in user cognition. We pr…