Paper Citation Record · LEDGER

Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2210.05528.

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

pith.paper-citation-record.v1
2210.05528 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:24:38.551893Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:35:33.622818Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ae2d43c6-3a9b-4fc2-b91d-8b0e08682172 · inbound

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition cites this paper.

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:43:25.482806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ed603987-1dac-419a-b42e-283570efbcbd · inbound

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees cites this paper.

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:53:21.428501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation acf24692-6f80-49f5-a447-fc4286a2583b · inbound

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble cites this paper.

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:25:19.576183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d3868f9-0622-47a1-b1f2-77758276ec37 · inbound

KiC: Keyword-inspired Cascade for Cost-Efficient Text Generation with LLMs cites this paper.

KiC: Keyword-inspired Cascade for Cost-Efficient Text Generation with LLMs Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:38.551893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5683305e-00df-41a8-86d4-f82b6c13c97d · inbound

T-TAMER: Provably Taming Trade-offs in ML Serving cites this paper.

T-TAMER: Provably Taming Trade-offs in ML Serving Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-04T14:57:00.226625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e540af78-fd84-4789-bbe9-9fc5251aa08f · inbound

Select to Think: Unlocking SLM Potential with Local Sufficiency cites this paper.

Select to Think: Unlocking SLM Potential with Local Sufficiency Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:56:27.659040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 730001d4-5c11-4ad9-bbd2-2cce57c62506 · inbound

Select to Think: Unlocking SLM Potential with Local Sufficiency cites this paper.

Select to Think: Unlocking SLM Potential with Local Sufficiency Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:35:33.624593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.