Conversation Tree Architecture: A Structured Framework for Context-Aware Multi-Branch LLM Conversations
Large language models (LLMs) are increasingly deployed for extended, multi-topic conversations, yet the flat, append-only structure of current conversation interfaces introduces a fundamental limitation: all context accumulates in a single unbounded window, causing topically distinct threads to bleed into one another and progressively degrade response quality. We term this failure mode logical context poisoning. In this paper, we introduce the Conversation Tree Architecture (CTA), a hierarchical framework that organizes LLM conversations as trees of discrete, context-isolated nodes. Each node maintains its own local context window; structured mechanisms govern how context flows between pa...
| Authors | Pranav Hemanth, Sampriti Saha |
|---|---|
| Primary category | cs.CL |
| Published | 22 March 2026 |
| Last updated at source | 22 March 2026 |
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