5 citations · 5 across the 6 of their papers we have counts for
6 papers
Reading Task Failure Off the Activations: A Sparse-Feature Audit of GPT-2 Small on Indirect Object Identification
Mahdi Nasermoghadasi
We report a small, reproducible audit of which sparse-autoencoder (SAE) features of GPT-2 small fire differently on failed versus successful trials of the Indirect Object Identific…
What Twelve LLM Agent Benchmark Papers Disclose About Themselves: A Pilot Audit and an Open Scoring Schema
Mahdi Naser Moghadasi, Faezeh Ghaderi
We read twelve well-known LLM agent benchmark papers and recorded, dimension by dimension, what each paper actually says about how its evaluation was run. The motivation came from…
Cross-Paradigm Knowledge Distillation: A Comprehensive Study of Bidirectional Transfer Between Random Forests and Deep Neural Networks for Big Data Applications
Mahdi Naser Moghadasi
The exponential growth of big data has intensified the need for efficient and interpretable machine learning models that can handle diverse data characteristics while maintaining c…
Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics
Mahdi Naser-Moghadasi
Query optimization in big data analytics remains computationally expensive, particularly for resource-constrained environments where traditional optimizers fail to satisfy memory a…
Neural Activation Patterns Across Language Model Architectures: A Comprehensive Analysis of Cognitive Task Performance
Mahdi Naser-Moghadasi, Faezeh Ghaderi
This paper presents a comprehensive analysis of neural activation patterns across six distinct large language model (LLM) architectures, examining their performance on twelve cogni…
Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models
Mahdi Naser Moghadasi, Faezeh Ghaderi
Despite the remarkable success of transformer architectures in natural language processing, their scalability limitations remain poorly understood through systematic empirical anal…