most citedDeep Forecast: Deep Learning-based Spatio-Temporal Forecasting

96 citations · 96 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2026

A Later Test Set Is Not a New Domain: Pretraining Familiarity Survives a Contamination-Free Hold-Out

Mahdi Naser Moghadasi, Faezeh Ghaderi

Time-series foundation models are evaluated almost exclusively on public archives that predate them, so a strong score cannot be separated from having seen the test set during pret…

cs.LG2026

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…

cs.CL2026

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…

cs.LG2026

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…

cs.LG201796 cited

Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting

Amir Ghaderi, Borhan M. Sanandaji, Faezeh Ghaderi

The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL)and in particular, Recurrent Neural Networks(RNNs). Motivated by recent advances in re…