Paper Citation Record · LEDGER

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation

As of 9 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2607.20478.

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

pith.paper-citation-record.v1
2607.20478 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:49:12.837047Z

measured 9 of 9 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 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 a464b027-409b-4e88-a1a4-04b8240ac37c · outbound

This paper cites GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.017207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 855481c1-18f7-418e-b03f-9c95ccaf5351 · outbound

This paper cites Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.245983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8caa8f3c-b07e-4e61-b0f8-f19a547d8829 · outbound

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

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.375671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 422e51b4-7d45-4847-81fa-fe289be0a411 · outbound

This paper cites Is Self-Repair a Silver Bullet for Code Generation?.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Is Self-Repair a Silver Bullet for Code Generation?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.672103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b49c4601-a781-4cf6-a0cf-93e34772ddea · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation ReAct: Synergizing Reasoning and Acting in Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.759614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4e731b-e311-403d-9aa8-7ddabf98f56b · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.444400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c0c35bf-6330-4366-8984-6c40c59d2e2c · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Self-Refine: Iterative Refinement with Self-Feedback

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.577541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 241160ee-1cc2-40b7-a564-dab56380ec8e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Evaluating Large Language Models Trained on Code

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.105331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d91454f-89b8-451b-8faf-c2b3da0b275e · outbound

This paper cites Generate Ter- raform HCL.

Verifier-First Evaluation of Agentic LLMs for Infrastructure-as-Code Generation Generate Ter- raform HCL

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T12:49:12.837047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.