🔑 Keywords: reinforcement learning, policy optimization, self-evolving agents, video comprehension, multi-task learning, large language models, spatial intelligence, geometric optimization, reasoning, visual representation, image editing

1. Agentic Reinforced Policy Optimization
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📋 Summary: This paper introduces a novel approach to reinforcement learning that focuses on agentic behavior optimization. The method improves policy learning by incorporating agent-specific objectives and demonstrates enhanced performance in complex decision-making scenarios with 14 authors contributing to this research.

2. A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence
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📋 Summary: This comprehensive survey explores the development of self-evolving AI agents and their potential path toward artificial super intelligence. The research examines current capabilities, limitations, and future directions in autonomous agent development with contributions from 27 authors.

3. ARC-Hunyuan-Video-7B: Structured Video Comprehension of Real-World Shorts
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📋 Summary: This work presents a 7B parameter model for structured video comprehension, specifically designed for real-world short videos. The system demonstrates advanced capabilities in understanding video content and extracting meaningful information from complex visual sequences.

4. Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning
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📋 Summary: This research introduces a novel multi-task learning approach that leverages representation-level task saliency. The method improves learning efficiency across multiple tasks by identifying and utilizing shared representations more effectively.

5. SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment
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📋 Summary: This paper presents a family of efficient large language models specifically designed for local deployment. The models achieve high performance while maintaining low computational requirements, making them suitable for edge devices and resource-constrained environments.

6. Reconstructing 4D Spatial Intelligence: A Survey
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📋 Summary: This comprehensive survey examines the reconstruction of 4D spatial intelligence in AI systems. The research explores temporal-spatial understanding and its applications in robotics, autonomous systems, and computer vision with 11 authors contributing to this work.

7. Geometric-Mean Policy Optimization
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📋 Summary: This research introduces a novel policy optimization method based on geometric mean principles. The approach improves learning stability and convergence in reinforcement learning scenarios with 12 authors contributing to this work.

8. Diversity-Enhanced Reasoning for Subjective Questions
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📋 Summary: This paper presents a framework for enhancing reasoning capabilities on subjective questions through diversity-based approaches. The method improves model performance on complex reasoning tasks with 4 authors contributing to this research.

9. Region-based Cluster Discrimination for Visual Representation Learning
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📋 Summary: This research introduces a novel approach to visual representation learning using region-based cluster discrimination. The method improves feature learning and representation quality in computer vision tasks with 12 authors contributing to this work.

10. GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset
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📋 Summary: This paper presents a large-scale dataset of 1.5 million GPT-generated images for image editing research. The dataset provides valuable resources for training and evaluating image editing models with 7 authors contributing to this work.