Beyond the Context Window: An Adaptive Entropy-Based Routing Framework for Hybrid Retrieval and Long-Context Language Models

arXiv:2609.35831 · cs.CL · Submitted 2026-09-23 · Read on arXiv

cs.CL

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• RAG — 51× in this paper · explained in 3 episodes
• Accuracy — 26× in this paper · explained in 1 episode
• Benchmark — 20× in this paper · explained in 2 episodes
• Hallucination — 12× in this paper · explained in 3 episodes
• Entropy-Driven Adaptive Router — 3× in this paper
• Uncertainty Quantification — 3× in this paper · explained in 8 episodes
• KV cache — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Modular Components — 1× in this paper · explained in 2 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Two-Stage Architecture — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Llama 2: Open Foundation and Fine-Tuned Chat Models
• GPT-4 Technical Report
• Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
• A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
• M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
• Retrieval-Augmented Generation for Large Language Models: A Survey
• LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
• RouteLLM: Learning to Route LLMs with Preference Data
• RouterBench: A Benchmark for Multi-LLM Routing System
• Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering