Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.10930.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T11:33:24.660158Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T05:19:45.781488Z
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 0bfe4785-404e-435e-bc3c-87426261052b · inbound
LLM-AutoDiff: Auto-Differentiate Any LLM Workflow cites this paper.
LLM-AutoDiff: Auto-Differentiate Any LLM Workflow Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T11:33:24.660158Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11a0699d-8b6a-468d-ba08-696ebbd53d14 · inbound
Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge cites this paper.
Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:05:36.753644Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 125093d4-d047-463e-a53e-f10a5fe0ea33 · inbound
Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models cites this paper.
Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:44:49.988365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c25b548-3a11-4063-bf2b-e2d8a7158111 · inbound
Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.
Learning, Fast and Slow: Towards LLMs That Adapt Continually Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T05:07:18.428439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ffce0901-474c-4101-b6df-bd29879ba9dc · inbound
Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.
Learning, Fast and Slow: Towards LLMs That Adapt Continually Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T05:19:45.785129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.