Papers with length-based models

1 papers
FLARE: Fine-Grained Length-Aware Routing for Resource-Efficient Heterogeneous LLM Serving (2026.acl-long)

Copied to clipboard

Challenge: Existing routers lack fine-grained resource awareness across deployment settings, which degrades efficiency metrics in real-world serving.
Approach: They propose a length-centric, resource-aware multi-LLM routing framework that uses length-based models to estimate per-query latency and cost.
Outcome: Experiments show that FLARE reduces latency and cost by up to 68% and 75% while maintaining competitive accuracy.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations