arXiv Machine Learning By Yixian Shen, Zhiheng Yang, Qi Bi, Changshuo Wang, Shuai Wang, Jia-Hong Huang, George Floros, Prayag Tiwari, Anuj Pathania

Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning

Read the original on arXiv Machine Learning →

arXiv:2606. 02842v1 Announce Type: new Abstract: Multimodal spatial reasoning often relies on long chains of intermediate textual and visual thoughts, where accumulating visual tokens and dense cross-modal attention incur substantial computation and memory overhead.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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arXiv:2607. 11436v1 Announce Type: new Abstract: Vision-language models increasingly succeed on multimodal reasoning benchmarks, yet their visual evidence often becomes unstable once it enters the language stack, weakening evidence-grounded reasoning.

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