Paper Citation Record · LEDGER

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation

As of 19 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 4 inbound Pith citation observations for arXiv:2412.15298.

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

pith.paper-citation-record.v1
2412.15298 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:01:22.032652Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:43:26.773582Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:35:49.803600Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy6
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 33505e2b-e0f1-476b-9dd0-b5567c2d35b2 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation A Comprehensive Overview of Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.914803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5df2753b-4781-433b-bffc-69ab70202a16 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.922532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 099164e1-a8bd-457d-8a8a-807d7b4b7b82 · outbound

This paper cites Can an unsupervised clustering algorithm re produce a catego- rization system? In Proceedings of the 5th ACM International Conference on AI in Finance, pages 213–221, 2024.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Can an unsupervised clustering algorithm re produce a catego- rization system? In Proceedings of the 5th ACM International Conference on AI in Finance, pages 213–221, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.428379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1878ef86-c5fb-42e5-88c1-8fdeeba3d7e1 · outbound

This paper cites Human-calibrate d automated testing and validation of generative language models: An overview.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Human-calibrate d automated testing and validation of generative language models: An overview

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.407632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ef7d701-b159-4d06-8586-750fabea96ea · outbound

This paper cites How to choose a t hreshold for an evaluation metric for large language models, 2024.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation How to choose a t hreshold for an evaluation metric for large language models, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.384672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 462d8068-cb13-4302-a522-efa972e1be84 · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.960419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 704fc6ff-9df9-479d-a19c-df556e83c010 · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.971357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5105474f-e8a6-483c-aee5-f50ed0c5cbf7 · outbound

This paper cites Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.978252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89de5ff8-6d67-42be-9eef-db2eb56a8c67 · outbound

This paper cites Lynx: An Open Source Hallucination Evaluation Model.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Lynx: An Open Source Hallucination Evaluation Model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.990131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3807932-4338-43f7-a734-d1abdf327ab2 · outbound

This paper cites Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:21.998399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56942437-dec7-4fe3-9b22-49bf6b255150 · outbound

This paper cites Dspy guardrails: Building safe ll m applications via self- reﬁning language model pipelines.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Dspy guardrails: Building safe ll m applications via self- reﬁning language model pipelines

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.364078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a28ef56c-fa48-4288-bacb-cd30988bde59 · outbound

This paper cites Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:22.009758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 861fef18-8df1-45c1-bf8d-008d652bf422 · outbound

This paper cites Optuna: A next-generation hyperparameter optimiz ation framework.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Optuna: A next-generation hyperparameter optimiz ation framework

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.344131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c8302609-f110-4f57-8e79-b037138b71c1 · outbound

This paper cites Ragas: Automated Evaluation of Retrieval Augmented Generation.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Ragas: Automated Evaluation of Retrieval Augmented Generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T12:01:22.025506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae1b5330-cc1b-4245-88db-5d7c768385a0 · outbound

This paper cites Fin e-tuning and prompt op- timization: Two great steps that work better together.

A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation Fin e-tuning and prompt op- timization: Two great steps that work better together

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:01:22.318380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 9fda36b6-16e5-4f65-a47e-93d2b28a15bd · inbound

Data Diversification Methods In Alignment Enhance Math Performance In LLMs cites this paper.

Data Diversification Methods In Alignment Enhance Math Performance In LLMs A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:26.773582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dc5b067-9875-4d2b-bd40-fa61ba0030e2 · inbound

Toxicity-Aware Few-Shot Prompting for Low-Resource Singlish Translation cites this paper.

Toxicity-Aware Few-Shot Prompting for Low-Resource Singlish Translation A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:03:24.474243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 783859c4-2f48-4371-9601-93430e7dd6e7 · inbound

FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts cites this paper.

FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:35:49.809037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a27738a-a448-4059-bf05-c18fee98723b · inbound

From Errors to Rules: Iterative Prompt Optimization for Text Classification cites this paper.

From Errors to Rules: Iterative Prompt Optimization for Text Classification A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T11:09:22.275369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.