Paper Citation Record · LEDGER

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing

As of 20 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2608.08528.

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

pith.paper-citation-record.v1
2608.08528 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:36:54.867058Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 63c66046-de77-4e01-bb1e-5ae669821259 · outbound

This paper cites Clio: Privacy-Preserving Insights into Real-World AI Use.

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing Clio: Privacy-Preserving Insights into Real-World AI Use

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.828736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad59fc0d-6f6e-4021-a26e-001093b13a74 · outbound

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

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.834239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a2c108c-2b01-4375-8d53-6466c124d5d7 · outbound

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

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing RouteLLM: Learning to Route LLMs with Preference Data

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.838768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e68eff5-f8e7-4635-9969-f8f2c68ee57b · outbound

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

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.843239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5378deae-c700-45fe-8538-ecfab3c8a4c1 · outbound

This paper cites AutoMix: Automatically Mixing Language Models.

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing AutoMix: Automatically Mixing Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.849349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f57e2d6-804d-47f0-98e9-a51b9c707e97 · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing Large Language Model Routing with Benchmark Datasets

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.854111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fab5987-9bca-4616-a59f-3101c50d39a4 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.858945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6be76008-de74-4409-8fb3-2880aecad84c · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing Evaluating Large Language Models Trained on Code

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.862952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08e113c1-146d-40cc-95a6-c3ab85dd38f0 · outbound

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

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T04:36:54.867058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.