SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations
Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing routers are effective in single-turn settings, they do not directly transfer to multi-turn dialogue, where routing performance critically depends on how historical context is segmented, retained, and incorporated into the current prompt. This introduces two fundamental challenges: preventing information loss and information confusion during context construction, and evaluating routing quality without conflating model selection with prompt cons
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- FuzzyOverlapping authors or contributors · 62%Kong/kong →
“Shared author/contributor keys: kong”
- FuzzyOverlapping authors or contributors · 62%ray-project/ray →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%rasbt/LLMs-from-scratch →
“Shared author/contributor keys: yin”
- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- LinkedLinked via arxiv author · 85%Ningyu Wang →
“SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations”
- LinkedLinked via arxiv author · 85%Yuchen Li →
“SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations”
- LinkedLinked via arxiv author · 85%Rui Kong →
“SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations”
- LinkedLinked via arxiv author · 85%Xinran Chen →
“SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations”