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cs.CV2026
Evian: Towards Explainable Visual Instruction-tuning Data Auditing
Zimu Jia, Mingjie Xu, Andrew Estornell +1
The efficacy of Large Vision-Language Models (LVLMs) is critically dependent on the quality of their training data, requiring a precise balance between visual fidelity and instruct…
cs.CV2025
Better Reasoning with Less Data: Enhancing VLMs Through Unified Modality Scoring
Mingjie Xu, Andrew Estornell, Hongzheng Yang +4
The application of visual instruction tuning and other post-training techniques has significantly enhanced the capabilities of Large Language Models (LLMs) in visual understanding,…