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SpatialCLI is proposed, a framework that teaches VLMs to reason with spatial tools and progressively internalize the specialist perceptual capabilities they provide and introduces SpatialCLI-Bench, a 516-example benchmark for compositional perception across localization, segmentation, depth, and pose.
This work progressively distill a bidirectional action-conditioned teacher into a causal student through teacher forcing and ODE distillation, and introduces LongForcing to align long student self-rollouts with an extended-horizon teacher, mitigating accumulated distribution shift and autoregressive drift.
ReVEAL consistently outperforms both closed-source and open-source state-of-the-art methods across extensive experiments and shows that explicitly verifying evidence sufficiency, rather than stopping at semantic relevance, retrieves the decisive clues that prior methods miss and yields more reliable long-video reasonin...
DAER maintains domain-isolated lightweight experts while keeping the pretrained Video-MLLM backbone frozen, thereby decoupling domain-specific adaptation from the general multimodal knowledge of the pretrained model, and introduces adaptive domain merging to improve parameter scalability and a two-stage optimization st...
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