3 papers
cs.LG2026
SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
Kexian Tang, Jiani Wang, Shaowen Wang +1
While large language models (LLMs) are pretrained on massive amounts of data, their knowledge coverage remains incomplete in specialized, data-scarce domains, motivating extensive…
cs.AI2025
LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?
Kexian Tang, Junyao Gao, Yanhong Zeng +6
Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning across multiple sequential step…
cs.CV2025
Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editing
Xiangyu Zhao, Peiyuan Zhang, Kexian Tang +10
Large Multi-modality Models (LMMs) have made significant progress in visual understanding and generation, but they still face challenges in General Visual Editing, particularly in…