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TTR-Compressor is evaluated as the compressor for block-wise sparse attention and the visual token merger for multimodal large language models and improves RULER performance over attention-based compressors by a large margin.
This work proposes Interleaved Distillation and Reinforcement Learning (IDRL), a novel post-training paradigm that tightly integrates on-policy distillation and reinforcement learning within a single training loop and enables more effective knowledge transfer, greater optimization stability, and more precise credit ass...
WorkDrive is proposed, a framework that constructs perception-grounded causal reasoning for work zones and aligns it with trajectory prediction and achieves progressive improvement over the trajectory-only baseline.
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