@inproceedings{yao-etal-2026-arc,
    title = "{ARC}: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents",
    author = "Yao, Yilun  and
      Huang, Shan  and
      Dai, Elsie  and
      Tan, Zhewen  and
      Duan, Zhenyu  and
      Jia, Shousheng  and
      Jiang, Yanbing  and
      Yang, Tong",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.930/",
    pages = "18644--18659",
    ISBN = "979-8-89176-395-1",
    abstract = "Large language models are increasingly deployed as research agents for deep search and long-horizon information seeking, yet their performance often degrades as interaction histories grow. This degradation, known as context rot, reflects a failure to maintain coherent and task-relevant internal states over extended reasoning horizons. Existing approaches primarily manage context through raw accumulation or passive summarization, treating it as a static artifact and allowing early errors or misplaced emphasis to persist. Motivated by this perspective, we propose ARC, which is the first framework to systematically formulate context management as an active, reflection-driven process that treats context as a dynamic internal reasoning state during execution. ARC operationalizes this view through reflection-driven monitoring and revision, allowing agents to actively reorganize their working context when misalignment or degradation is detected. Experiments on challenging long-horizon information-seeking benchmarks show that ARC consistently outperforms passive context compression methods, achieving up to an 11{\%} absolute improvement in accuracy on BrowseComp-ZH with Qwen2.5-32B-Instruct."
}