arXiv:2609.38716v1 Announce Type: cross
Abstract: Large Vision-Language Models (LVLMs) have made remarkable progress across visual perception tasks, yet spatial reasoning remains a persistent weaknes...
By Rafi Ibn Sultan, Xiangyu Zhou, Md. Sajid Alam Chowdhury, Chengyin Li, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu
MV-STRIDE is a Multi‑View hierarchical Spatial Reasoning dataset that models dependencies among perception, scene understanding, and contextual reasoning to support 3D spatial cognition. It introduces a QA generation pipeline that enforces cross‑view constraints, producing multi‑level reasoning tasks with chain‑of‑thought supervision. Experiments show that training on MV‑STRIDE yields state‑of‑the‑art performance on multi‑view spatial benchmarks, enabling MLLMs to reason robustly across diverse viewpoints.
By Jin Xu, Xiaojian Huang, Zhuodong Luo, Zhihong Zhang, Xin Liu, Jiansheng Wei, Xinzhi Wang, Jie Zhao, Xuejin Chen
arXiv:2511. 07403v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved remarkable progress in vision-language tasks, but continue to struggle with spatial reasoning.
By Hunar Batra, Haoqin Tu, Hardy Chen, Yuanze Lin, Cihang Xie, Ronald Clark
arXiv:2609.24813v1 Announce Type: new
Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in multimodal tasks, yet they still exhibit poor ability in spatial reasoning....
By Haoran Sun, Jingqi Xu, Yanhui Li, Enci Liu, Kaidi Xu, Yanwei Liu
Soft Spatial Reasoning introduces a post‑training framework for Large Vision‑Language Models that replaces hard, token‑by‑token chain‑of‑thought reasoning with a soft, continuous state formed by mixing token embeddings at each intermediate step. The method employs AdaptSoft, a controller that adjusts the degree of softness based on hidden states and predictive uncertainty, guided by a gradient‑alignment learning objective that requires no intermediate supervision. Experiments on diverse spatial benchmarks show that this approach outperforms both hard and fixed‑soft chain‑of‑thought baselines and several existing LVLMs.
By Rafi Ibn Sultan, Md. Sajid Alam Chowdhury, Saleh Zare Zade, Chengyin Li, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu
arXiv:2606. 11719v1 Announce Type: cross Abstract: Spatial reasoning remains a persistent challenge for multimodal large language models (MLLMs).
By Enhan Zhao, Wei Wu, Yuanrui Zhang, Xueliang Zhao, Di He