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Paper Citation Record · LEDGER

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge?

As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.17015.

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

pith.paper-citation-record.v1
2507.17015 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:02:21.839624Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

35 of 35 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved32
  • parse uncertain0
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External citation measurements

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Outbound references

Observation 4b92e2cb-d69e-4275-a323-e9cd285741d7 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Constitutional AI: Harmlessness from AI Feedback

Reference 1

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Observation 7c29cf48-4c00-4b26-80f0-b9c83b4cd5ec · outbound

This paper cites LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks

Reference 2

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Observation 0aeb6484-a2ca-438d-bea8-95f5b98646f7 · outbound

This paper cites The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs

Reference 3

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source=arxiv_source observed=2026-08-06T15:02:21.683550Z digest=sha256:e8b94a3a8cbe981b0248a30280cf9e3691b175310d8e0b8e8ccb0dfd4397c3ac

Observation 696328f2-9cca-404c-8a92-1d7326ee8e1f · outbound

This paper cites ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate

Reference 4

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Observation afa20a44-b53b-4b25-aa8f-c86217d602f9 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Evaluating Large Language Models Trained on Code

Reference 5

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Observation 6dbdedf3-427b-4f63-8e0a-0a713190021e · outbound

This paper cites Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Reference 6

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source=arxiv_source observed=2026-08-06T15:02:21.691005Z digest=sha256:2a5013e6ab6a8a94a6953d2461d19af29c036b52cb4470f1907357a94522243d

Observation dff28471-97c9-4e20-ad21-c8e534565395 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Training Verifiers to Solve Math Word Problems

Reference 8

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Observation 37dccd96-8a34-4014-9f69-893d509bccae · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 9

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Observation 1d85940f-12fb-4336-ad9b-4328bb595a0b · outbound

This paper cites Liang, and Tatsunori B.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Liang, and Tatsunori B

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 203ce50a-051b-4620-9a07-382191bbfa13 · outbound

This paper cites RARR: Researching and Revising What Language Models Say, Using Language Models.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? RARR: Researching and Revising What Language Models Say, Using Language Models

Reference 11

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source=arxiv_source observed=2026-08-06T15:02:21.701968Z digest=sha256:0ddf837ff54dce7c835febc30809865ec2754c1719a4fafde4588a9cdd3fbecc

Observation d0c9a754-01be-4817-b58d-b83e65452dd9 · outbound

This paper cites an unresolved cited work.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Unresolved cited work

Reference 12

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Observation 085a6dbf-5564-4730-9830-9f82813a9273 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Measuring Coding Challenge Competence With APPS

Reference 13

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Observation c07ab589-2337-441c-99f3-1e134e3650a2 · outbound

This paper cites Human Feedback is not Gold Standard.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Human Feedback is not Gold Standard

Reference 14

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Observation f0871de8-dcc8-40d7-b89e-cd471039a507 · outbound

This paper cites Evaluating Robustness of Reward Models for Mathematical Reasoning.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Evaluating Robustness of Reward Models for Mathematical Reasoning

Reference 15

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Observation 0b126402-104c-43ad-8713-555261521a8b · outbound

This paper cites The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

Reference 16

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source=arxiv_source observed=2026-08-06T15:02:21.712413Z digest=sha256:180c8a923e6fe027ad5d2e3914d80064424e4a075a80aca51a9624cce8957f00

Observation fc74ba33-dc17-429c-814b-539bd0c51aea · outbound

This paper cites RewardBench: Evaluating Reward Models for Language Modeling.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? RewardBench: Evaluating Reward Models for Language Modeling

Reference 17

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Observation c71181a0-27cd-4845-8b1f-fd2b38befa45 · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 18

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Observation 02a25f2e-4576-4db9-b428-263a8a3f826c · outbound

This paper cites Tool-Augmented Reward Modeling.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Tool-Augmented Reward Modeling

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2fcb3709-63c9-413c-8b21-1428d29b4c64 · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 20

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Observation d199b5c7-5a15-4309-a036-690b3351ff3b · outbound

This paper cites Let's Verify Step by Step.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Let's Verify Step by Step

Reference 21

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Observation d14add69-cedc-4091-8fc2-9d9376d3dc99 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 22

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Observation 3d4ab151-4a94-4f2c-8786-c220d4fce449 · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 23

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source=arxiv_source observed=2026-08-06T15:02:21.727560Z digest=sha256:e56c8736653b3451ba1eafb927bc0d807e5b63371e17575438e64fe36957e0ab

Observation 178e20b4-6ba5-470c-8500-9a67a4705c4a · outbound

This paper cites FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Reference 24

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Observation eb1d00de-c94e-4ac2-89c8-b627869962e4 · outbound

This paper cites an unresolved cited work.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ff84316f-d482-4e36-9d8b-12c0ac14e873 · outbound

This paper cites LLM Evaluators Recognize and Favor Their Own Generations.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? LLM Evaluators Recognize and Favor Their Own Generations

Reference 26

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Observation 320efc4c-9de5-4aea-b116-406fdd698f44 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 27

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Observation b3a45513-346b-4b52-a5cd-055cc172cc3d · outbound

This paper cites Christiano.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Christiano

Reference 28

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raw_fallback, observed 2026-08-06T15:02:22.036908Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4684ed4a-4017-48d3-b2cb-e6924d757c0c · outbound

This paper cites an unresolved cited work.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T15:02:21.741016Z digest=sha256:ce03f09f43d8f48bf9c3486971dc41f4de45ac998fb74b2136040f81b2a62a1e

Observation 5774f7bf-1076-45a0-be24-1b64bd10c7e4 · outbound

This paper cites Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models

Reference 30

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source=arxiv_source observed=2026-08-06T15:02:21.742842Z digest=sha256:5f786b337a1c3e07bceece8c614242f14793dcde58199dcc5a75e37eb99ca6cf

Observation fb4bc773-9123-468b-b86b-bc067f993f38 · outbound

This paper cites Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers

Reference 31

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Observation 2fce3b73-9d30-4887-902c-f4726afa870e · outbound

This paper cites Long-form factuality in large language models.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Long-form factuality in large language models

Reference 32

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Observation fec041df-7f0e-4951-9943-7ada0188cf39 · outbound

This paper cites GPT Can Solve Mathematical Problems Without a Calculator.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? GPT Can Solve Mathematical Problems Without a Calculator

Reference 33

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Observation 3cafa3fe-b09b-43de-abd6-af3bd125bee2 · outbound

This paper cites Evaluating Large Language Models at Evaluating Instruction Following.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Evaluating Large Language Models at Evaluating Instruction Following

Reference 34

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Observation e2f3ce1e-5da4-49ee-80e9-26575453cac5 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 35

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Observation efc4f697-2a27-46e7-8e10-92199032e735 · outbound

This paper cites Agent-as-a-Judge: Evaluate Agents with Agents.

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? Agent-as-a-Judge: Evaluate Agents with Agents

Reference 36

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Pith citing papers

No inbound Pith citation observations are available.