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Paper Citation Record · LEDGER

Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2501.13080.

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

pith.paper-citation-record.v1
2501.13080 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:46:00.686918Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:44:21.927874Z

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 1ffaad9f-2173-4378-9925-b5e20436eca6 · inbound

Position Paper: Metadata Enrichment Model: Integrating Neural Networks and Semantic Knowledge Graphs for Cultural Heritage Applications cites this paper.

Position Paper: Metadata Enrichment Model: Integrating Neural Networks and Semantic Knowledge Graphs for Cultural Heritage Applications Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:00.686918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:00.686918Z digest=sha256:d45553dab83d9ea7a10acf3d1b5dab197fdab1d0469da937ba66284989a277de

Observation 08cddfeb-c7d8-4643-b109-c0b071d77632 · inbound

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety cites this paper.

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T10:24:26.440712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:24:26.440712Z digest=sha256:f99018b1ab40a1dd7bc8d74f4c4b41cf112beef22bdc5b90733f264eab72d89a

Observation 697e8218-4d78-422f-9940-063110834aaa · inbound

SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models cites this paper.

SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T15:52:42.297827Z

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.

source=pdf_text observed=2026-05-18T15:52:27.652484Z digest=sha256:85287bc605ca5d127eb7927d500ba847eeaa1cca183b3e4f2795fb3b5bc583b4

Observation ee7ca27d-2cd5-4da4-a1ef-234149c73a75 · inbound

From Refusal to Recovery: A Control-Theoretic Approach to Generative AI Guardrails cites this paper.

From Refusal to Recovery: A Control-Theoretic Approach to Generative AI Guardrails Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:44:21.930174Z

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.

source=pdf_text observed=2026-05-21T20:42:40.823721Z digest=sha256:1e40a731efb85a478fa8bf7dd354da6ffa85d85b006d31b436da3b28dafc7d97