Author

Jie Li

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#artificial intelligence Preprint Oct 2026

Revisiting Triplet Contrastive Learning for 3D Shape Understanding

In multi-modal 3D pre-training, aligning 3D shapes, their 2D image counterparts, and language descriptions has made tremendous progress. However, we find that supervision from rendered images is unreliable, the semantics encoded in synthetic views are distorted due to domain gap, self-occlusion, and rendering artifacts...

Chao-Yang Zhu, Zhe Liao, Jia-Yi Zhang et al. · 0 citations

Preprint Jul 2026

Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation

Modality Subspace Activation (MSA) is proposed, a training-free inference-time framework that uses Singular Value Decomposition (SVD) to estimate modal activation strengths and dynamically balances modal projections in the last hidden state, effectively restoring CMS across benchmarks.

Hongbo Jiang, Jie Li, Yunhang Shen et al. · 0 citations