Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2407.10817.
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 2026-08-09T10:26:06.997800Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T02:36:27.459119Z
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 2976c262-f0a4-454f-b32e-3bf84bdadcd8 · inbound
LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.
LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 234
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:08:35.575421Z
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 af6ecb3f-2016-40f0-95d1-db9311c2b413 · inbound
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons cites this paper.
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T10:26:06.997800Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 795ba532-f5e8-431e-a83c-0bb54cc36c61 · inbound
Towards an AI co-scientist cites this paper.
Towards an AI co-scientist Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 29
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T13:02:44.469756Z
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 23974def-50e9-40c3-b46c-5dc512e23a69 · inbound
A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety cites this paper.
A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:14:13.271655Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 240afa34-a1fe-46c9-a726-ea6ec02e62c6 · inbound
Do Biased Models Have Biased Thoughts? cites this paper.
Do Biased Models Have Biased Thoughts? Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:39:28.084796Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9da63934-2330-48fc-a9c6-0ad8e789d7aa · inbound
CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments cites this paper.
CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T20:36:50.269769Z
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 9fa42a41-edc6-4d17-ac23-407057dcd7dc · inbound
EvoSkill: Automated Skill Discovery for Multi-Agent Systems cites this paper.
EvoSkill: Automated Skill Discovery for Multi-Agent Systems Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T02:25:05.453288Z
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 bb20f579-9ca9-4c12-84b4-8ce6d72d0dbc · inbound
CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks cites this paper.
CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T02:36:27.460931Z
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.