1 citations · 1 across the 3 of their papers we have counts for
7 papers
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…
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines
Saleh Afroogh, Yasser Pouresmaeil, Yiming Xu +3
Large Language Models (LLMs) are rapidly reshaping academic research across the natural sciences, social sciences, and humanities, yet the scientific community lacks a comprehensiv…
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…
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…
AI Empathy Erodes Cognitive Autonomy in Younger Users
Junfeng Jiao, Abhejay Murali, Saleh Afroogh
Affective alignment in generative AI represents a systemic risk to the developmental autonomy of younger users. Although emotional mirroring is commonly seen as a hallmark of advan…
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…