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Recent multimodal deep search agents have advanced tool use and visual content retrieval, yet they still struggle to convert intermediate visual evidence into actionable guidance for subsequent search, limiting their effectiveness in long-horizon settings. To address this gap, we present Neos, a multimodal deep search...
While standard end-to-end baselines struggle to complete these logically demanding tasks, ACE achieves a 50% success rate in equation formation and a 70% success rate in constraint retrieval, demonstrating that explicit workflow reasoning and mask-mediated control offer a robust, practical route toward adaptable roboti...
XS-VLA is introduced, a lightweight framework that teaches tiny VLA policies "where to look" and "how to move" without increasing deployment-time model cost and shows that explicit spatial grounding and latent action-structure learning can make tiny VLA models effective for robotic manipulation.
LigBench is proposed, an automated evaluation benchmark that enables fine-grained and reliable evaluation of AI research ideas, consistently applicable across different generation distributions, and PAIR-IQ, a dataset tailored for training pairwise idea judgment models and serving as an auxiliary reference to support m...
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