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

1 citations · 1 across the 4 of their papers we have counts for

collaborators

14 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.AI2026

LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)

Ankai Hao, Ke Chen, Huan Li +1

Feature engineering remains a cornerstone of tabular data analysis, and Large Language Models (LLMs) have emerged as a promising paradigm for its automation, giving rise to LLM-pow…

cs.DL2026

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…

cs.CY20261 cited

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.LG2026

Entropy-Preserving Reinforcement Learning

Aleksei Petrenko, Ben Lipkin, Kevin Chen +4

Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn from exploration on their own trajector…