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Video generators may convincingly simulate real-world dynamics, but they often fail to understand the underlying causal relationships, revealing a critical gap in their reasoning capabilities.
LazyMCoT achieves training-free visual grounding that rivals traditional methods while cutting inference time, redefining efficiency in multimodal reasoning.
Projector Drift reveals a hidden vulnerability in omni-modal systems that can significantly impair audio retrieval, but a simple fine-tuning strategy can effectively address it.
Forget manual data curation – now LLMs can autonomously engineer training data that boosts student model performance by over 57%.
