الباحثون

Nikki Lijing Kuang

المنشورات 2

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Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning

Yuqing Zhou, Hong Wang, Manqing Mao وآخرون · 2026

Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level objectives or local token- and step-level signals, but rarely model inter-step semantic dependencies. This limits their ability to distinguish redundant steps from thos …

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Uni-LaDiR: Latent Diffusion Unifies Multimodal Reasoning

Multimodal models increasingly think with different modalities such as images, 3D point clouds, and robot states, not just text. Yet each modality is still encoded into its own representation space, creating a modality-switching gap whenever reasoning moves from one modality to another. In this paper, we introduce Uni- …

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