TreeAgent: Structure-Aware Memory Agent for Processing Long Hierarchical Data

arXiv:2611.13946v1 Announce Type: new Abstract: Practical Web applications increasingly require agents to interpret long conversations or documents. For inputs exceeding the context windows of large language models (LLMs), memory agents process segments sequentially and retain past information in bounded memory. However, they typically divide inputs into flat token segments without preserving structure or hierarchy, causing three limitations for structured data such as API responses or HTML documents. First, fixed-length segmentation can split fields of the same record, breaking their relation

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