LongSeeker: Elastic Context Orchestration for Long-Horizon Search Agents
Shanghai Jiao Tong University
Researchers from SJTU introduced LongSeeker (arXiv:2605.05191) addressing context explosion in long-horizon search agents via Context-ReAct: five adaptive operations (Skip, Compress, Rollback, Snippet, Delete) that dynamically reshape working memory based on relevance. LongSeeker, fine-tuned from Qwen3-30B-A3B, achieves 61.5% on BrowseComp and 62.5% on BrowseComp-ZH.
Why it matters
Active working-memory shaping is shown to outperform accumulating all trajectory data for long-horizon agents, providing a benchmark-validated approach to a core agent reliability bottleneck.
Importance: 2/5
Addresses a core long-horizon agent failure mode with quantified BrowseComp results