Multimodal Language Model Evaluator & Quality Assurance Auditor
Evaluated and audited multimodal large language model (LLM) outputs for high-precision Handwriting Synthesis and Refinement datasets. Reviewed complex visual data across diverse language scripts (including localized character sets and ligatures) to identify micro-glitches, alignment shifts, and stroke anatomy defects. Validated model outputs against strict quality matrices, managing edge cases in image clarity, visual legibility, and aesthetic consistency to refine computer vision training benchmarks.