Paper Citation Record · LEDGER

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2411.09837.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.09837 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:20:59.600931Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:26:26.443597Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy15
unresolved19
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e06222fe-04f0-4106-9270-087a113cfdb7 · outbound

This paper cites an unresolved cited work.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:21:00.361420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 61f994f7-8a2c-4b8a-943e-23cf6a21ac3d · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.464748Z

Source-reported events for the cited work

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Observation e7d02191-015c-47c3-a0b5-9fef5affbf81 · outbound

This paper cites an unresolved cited work.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.470272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 689bee86-f903-4a36-a6da-02c3d4f7cd29 · outbound

This paper cites Graph of Thoughts: Solving Elab- orate Problems with Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Graph of Thoughts: Solving Elab- orate Problems with Large Language Models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.338862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cdd0db40-0801-4216-b005-1ab44b91f93d · outbound

This paper cites Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.478656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f32d5ba-6d88-43a9-b718-09b640d8a9e4 · outbound

This paper cites Fru- galML: how to use ML prediction APIs more accurately and cheaply.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Fru- galML: how to use ML prediction APIs more accurately and cheaply

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.317294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 79722f8f-957a-41ec-a8e4-e720d025505a · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.486445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6318681-61bf-4aff-8b61-72ff304c87e8 · outbound

This paper cites Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.490706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b5a882b-fbb0-4261-8d76-237dac3145a0 · outbound

This paper cites Hassan et al.Towards AI-Native Software En- gineering (SE 3.0): A Vision and a Challenge Roadmap.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Hassan et al.Towards AI-Native Software En- gineering (SE 3.0): A Vision and a Challenge Roadmap

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.292799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7ca004db-54c3-4056-94a2-64257e65b06d · outbound

This paper cites org/abs/2410.06107.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models org/abs/2410.06107

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.506675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5531d296-31bb-4d53-97e1-170acb63ee8b · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Measuring Massive Multitask Language Understanding

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45637ee3-6b73-4a08-9d65-f74d76bef39c · outbound

This paper cites RouterBench: A Benchmark for Multi-LLM Routing System.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models RouterBench: A Benchmark for Multi-LLM Routing System

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77aec04a-f59f-4ab4-bfaa-8842d2e67ba0 · outbound

This paper cites Jiang et al.Mistral 7B.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Jiang et al.Mistral 7B

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.271016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 029a8c25-b688-4939-aab6-c9806c883702 · outbound

This paper cites LLM- Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models LLM- Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.250324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e6013a33-2f81-4cde-aef0-378e83e0ea67 · outbound

This paper cites Scaling Laws for Neural Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Scaling Laws for Neural Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.530628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5a32620-414d-407d-b442-0224e77c22b5 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.232432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 495c9e76-a693-4c0e-abf1-7817944fc501 · outbound

This paper cites MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.539328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f43c66aa-78ab-4cec-a543-eac266a908bf · outbound

This paper cites AutoMix: Automatically Mixing Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models AutoMix: Automatically Mixing Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.543597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f23a1f3-5c06-4e8c-8d33-64f9d133dcdc · outbound

This paper cites CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.548055Z

Source-reported events for the cited work

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Observation 2c604f91-74a2-4451-b3a5-c6eaaecdc238 · outbound

This paper cites The Chi-square test of indepen- dence.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models The Chi-square test of indepen- dence

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.206625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cf3233e0-549f-491c-accf-6423112c55c8 · outbound

This paper cites https://ai.meta.com/ blog/llama- 3- 2- connect- 2024- vision- edge- mobile- devices/ [Accessed: (Sept.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models https://ai.meta.com/ blog/llama- 3- 2- connect- 2024- vision- edge- mobile- devices/ [Accessed: (Sept

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.187758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d0bf1152-8ad7-46f3-b9b4-b6eb90747a6f · outbound

This paper cites RouteLLM: Learning to Route LLMs with Preference Data.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models RouteLLM: Learning to Route LLMs with Preference Data

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.559964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9850e86b-9713-4e00-bde8-1a517416d40f · outbound

This paper cites https://openai.com/index/hello- gpt-4o/.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models https://openai.com/index/hello- gpt-4o/

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.172126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6e13b4bf-a177-41ae-a8b6-f34c1d225274 · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Large Language Model Routing with Benchmark Datasets

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.569933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3491fe4-1b49-47ca-af45-3cac6cdec6bd · outbound

This paper cites https://huggingface.co/sentence-transformers/all- MiniLM-L12-v2.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models https://huggingface.co/sentence-transformers/all- MiniLM-L12-v2

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.149746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a51f4aa9-769d-4bcc-8c94-8b4e2529ea9e · outbound

This paper cites V oyager: An Open-Ended Em- bodied Agent with Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models V oyager: An Open-Ended Em- bodied Agent with Large Language Models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.121045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c9a03e5d-e11c-4124-b48c-2512e8df40eb · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.103147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 47f3f088-9b8d-4810-9c57-80885c47e504 · outbound

This paper cites Tabi: An Efficient Multi-Level Inference System for Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Tabi: An Efficient Multi-Level Inference System for Large Language Models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.084821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ad161b97-b771-42a4-a4f9-6560b93a0063 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Chain-of-thought prompting elicits reasoning in large language models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.069463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2b6b49b8-67c9-4b87-9dc5-5e0929c74823 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.590048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dc4546a-5dcb-4e0a-aea8-6ec6e4d717dd · outbound

This paper cites A Survey of Large Language Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models A Survey of Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.593301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94ff2458-385c-4a4d-9723-6808c3e0d34b · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.597115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dcc2037-329e-482e-be97-d62722ab4ad5 · outbound

This paper cites Judging LLM-as-a-judge with MT-bench and Chatbot Arena.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models Judging LLM-as-a-judge with MT-bench and Chatbot Arena

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:21:00.049017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation be36f968-bd60-45c4-82bb-18eaf446732c · outbound

This paper cites The Llama 3 Herd of Models.

Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models The Llama 3 Herd of Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T20:20:59.460818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3d539b07-bcb2-44f0-8418-7f9d9f4937d6 · inbound

Adaptive Minds: Empowering Agents with LoRA-as-Tools cites this paper.

Adaptive Minds: Empowering Agents with LoRA-as-Tools Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T09:26:26.443597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.