Researchers have introduced Glasseek, a novel framework designed to enhance the transparency and reproducibility of training deep search agents. The framework addresses challenges in data auditing, context compression mismatches, and evaluation contamination. Glasseek includes a verifiable trajectory curation pipeline, a Compaction-Managed GSPO (CM-GSPO) training method, and a modular anti-leakage plugin for evaluations. A 9B agent trained with Glasseek has demonstrated state-of-the-art performance among open-weight agents and surpasses proprietary agents on various deep research benchmarks. AI
IMPACT Sets a new state of the art for open-weight agents and improves evaluation rigor for deep search capabilities.
RANK_REASON The cluster describes a new research paper detailing a framework and methodology for training AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- CM-GSPO
- Connected Papers
- DagsHub
- Glasseek
- Gotit.pub
- Hugging Face
- Litmaps
- ScienceCast
- Scite
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