·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning7h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks7h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts7h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning7h◆FrontierChallenge: Evaluating Scientific Workflow Completion7h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier7h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising7h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic7h◆Omni Interaction Agent Technical Report7h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification7h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability7h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization7h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding7h◆Tracing Computation Density in LLMs7h◆Cultural Binding Heads in Language Models7h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training7h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models7h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning7h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection7h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation7h◆Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning7h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks7h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts7h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning7h◆FrontierChallenge: Evaluating Scientific Workflow Completion7h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier7h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising7h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic7h◆Omni Interaction Agent Technical Report7h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification7h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability7h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization7h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding7h◆Tracing Computation Density in LLMs7h◆Cultural Binding Heads in Language Models7h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training7h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models7h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning7h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection7h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation7h◆
News/Beyond Accuracy and Cost: Latency-Aware LLM Query Routing for Dynamic Workloads
arxiv
PublishedJuly 22, 2026 at 4:00 AM
▲bullish

Beyond Accuracy and Cost: Latency-Aware LLM Query Routing for Dynamic Workloads

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2607.18253v1 Announce Type: new Abstract: Modern language query routers improve inference efficiency by assigning each query to a model that balances response quality and monetary cost. However, current query routers are largely latency-agnostic and do not consider the generation latency exper

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#optimization#latency#inference#query-routing

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#optimization#latency#inference#query-routing

Related coverage

More from ARXIV
arxivBringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning7harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks7harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts7harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning7h
The Bubble Brief
WEEKLY

Read optimization insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews