Ehsaneddin Asgari

Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagnose their true reasoning abilities and chart meaningful progress toward human-like multimodal intelligence. Most existing evaluations focus on piecemeal or disconnected tasks, obscuring cr...

Tokenization fundamentally shapes NLP performance, affecting both efficiency and linguistic fidelity. While Byte Pair Encoding (BPE) underpins most Large Language Models (LLMs), its frequency-driven merges often disregard morpheme boundaries, yielding inconsistent and semantically opaque segmenta...