PolarSeeker is a research collective dedicated to exploring the absolute frontiers of LLM-based agents. We believe that truly intelligent agents require a systematic synergy across the entire stack—from high-quality data synthesis to long-horizon agentic reasoning.
We focus on building a comprehensive agentic ecosystem across four key dimensions:
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Data: Pioneering high-quality, synthetic, and expert-level data pipelines for agent training (e.g., OpenSeeker).
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Training: Developing advanced fine-tuning and alignment techniques specifically for reasoning agents.
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Context: Mastering long-horizon task management and infinite-context reasoning (e.g., LongSeeker).
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Harness: Building rigorous agentic frameworks to release the full potential of agentic capabilities.