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cs.CV2026
MechReason: Benchmarking Multi-Image Multi-Hop Reasoning in Mechanical Engineering
Tengyue Wang, Kang An, Chenxu Du +8
Despite significant progress in general visual question answering and cross-modal understanding, multimodal large language models still face a pronounced gap in evaluation for comp…
cs.CV2026
GRADE: Benchmarking Discipline-Informed Reasoning in Image Editing
Mingxin Liu, Ziqian Fan, Zhaokai Wang +13
Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natural images and shallow commonsense…
cs.CV2025
One RL to See Them All: Visual Triple Unified Reinforcement Learning
Yan Ma, Linge Du, Xuyang Shen +7
Reinforcement learning (RL) is becoming an important direction for post-training vision-language models (VLMs), but public training methodologies for unified multimodal RL remain m…