Latent Visual Contrastive Reasoning with Multi-Branch Exploration
Multimodal large language models have made substantial progress in visual question answering, but complex visual reasoning often requires locating and comparing multiple pieces of question-relevant visual evidence. Existing methods that move intermediate reasoning into the visual latent space usually follow a single linear reasoning trajectory, which can be limiting when multiple visual hypotheses or competing evidence regions are relevant. We propose Latent Visual Contrastive Reasoning, a branch-aware latent reasoning framework that generates multiple question-conditioned latent visual branches as soft hypotheses over image tokens. To train these branches, our method uses bounding-box ev...
| Authors | Kegeng Tang, Jingbo Wang, Yangming Zhang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 27 October 2026 |
| Last updated at source | 27 October 2026 |
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