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CDRRM: Contrast-Driven Rubric Generation for Reliable and Interpretable Reward Modeling
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A Simple Baseline for Unifying Understanding, Generation, and Editing via Vanilla Next-token Prediction
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How to Train Your Deep Research Agent? Prompt, Reward, and Policy Optimization in Search-R1
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MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning
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LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts
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ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
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CoBA-RL: Capability-Oriented Budget Allocation for Reinforcement Learning in LLMs
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Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory
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SpanNorm: Reconciling Training Stability and Performance in Deep Transformers
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EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience
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Silence the Judge: Reinforcement Learning with Self-Verifier via Latent Geometric Clustering
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Efficient Context Scaling with LongCat ZigZag Attention
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EditThinker: Unlocking Iterative Reasoning for Any Image Editor
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Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments
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Evaluating Object Hallucination in Large Vision-Language Models
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Decision-Making Context Interaction Network for Click-Through Rate Prediction
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Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction
