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While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-level guidance. On-policy self-distillation addresses this limitation by conditioning a self-teacher on privileged information to provide dense token-level supervision. Ho...
GeoAnchor decomposes 3D spatial information into three complementary components: position latents for object grounding, direction latents for relational orientation, and geometry latents for scene structure, and is introduced a collaborative training strategy that guides the model from local spatial perception to compr...
A PETL-based framework named UniGR is presented that unifies granularity and reliability for robust and efficient TPR, and a multi-granularity relational adapter (MRA) is designed to capture both coarse-grained global and fine-grained local relational features among tokens.
NaviDC-OCR introduces deformation-aware learning to incorporate geometric perception into VLMs and proposes an adaptive sampling mechanism for complex layout representation, and a content-structure decoupled learning strategy is developed to explicitly model formula grammars and table structures, enabling more effectiv...
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