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Paper Citation Record · LEDGER

Benchmarking Cognitive Biases in Large Language Models as Evaluators

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2309.17012.

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

pith.paper-citation-record.v1
2309.17012 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:34:00.009661Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T12:53:50.367532Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f899883b-0a27-470b-8d38-f46471bf40bf · inbound

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

LLM Evaluators Recognize and Favor Their Own Generations Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 10

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arxiv_id, observed 2026-05-22T18:44:28.816877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T18:44:28.766639Z digest=sha256:a9eb3c4252c26ac54df6dd3c0f6b0761000607e02ed317d7a6a39966d635625f

Observation ab7b2c8e-08ff-4d0d-838d-9aed89e9baa7 · inbound

Better & Faster Large Language Models via Multi-token Prediction cites this paper.

Better & Faster Large Language Models via Multi-token Prediction Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 9

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arxiv_id, observed 2026-05-16T12:26:09.810803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T12:26:09.731664Z digest=sha256:e3708b6ca6a273fcdec62ac5e52597d453a8ebcb31385751cde8c4c1fca9c876

Observation fc4e8733-be44-49d0-9fec-7d700a4c89f8 · inbound

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap cites this paper.

From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 64

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arxiv_id, observed 2026-05-23T19:08:20.988267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T19:07:21.016824Z digest=sha256:4d0e6d8d6e3642b3ce3bc712d21521f0db6a28da6ed648e7410c24864e263547

Observation 5a3abb5e-cfdd-4880-860c-93fc57e331bd · inbound

A Survey on LLM-as-a-Judge cites this paper.

A Survey on LLM-as-a-Judge Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 69

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arxiv_id, observed 2026-05-23T17:35:44.032235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T17:33:13.394338Z digest=sha256:4b2137b440bee59a67a1609a2c877c557946763e88ef3ff04a36b32882221423

Observation 9e50b7f7-7e23-4f03-9e13-a8302fd0db5b · 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 Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 116

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verified exact
arxiv_id, observed 2026-05-11T23:08:37.018788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:52036073612bc686f0e0926077d0b2166db69c032284b7620dfda55d84a48dd4

Observation 6b7b52ec-d510-4b2a-ae3e-41f8d6522a8a · inbound

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models cites this paper.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 15

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no resolver link, observed 2026-08-10T19:51:25.722030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:51:25.722030Z digest=sha256:3770f5e5a450ea45f7b47be58f07bf64bdce8bbfe970424c693e44109451cd36

Observation 3bb4f7c7-5569-427d-a7e3-9a8fec855943 · inbound

Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer cites this paper.

Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 7

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no resolver link, observed 2026-08-16T12:34:00.009661Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:34:00.009661Z digest=sha256:da5f7ef134370a33abf1bcf92d42bdb996f2d72fc0b6e13d4de978aa09515db9

Observation 5648ec8d-639b-4df0-bcf0-3c04f82cfe5a · inbound

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward cites this paper.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 36

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no resolver link, observed 2026-08-16T11:01:39.832116Z

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source=arxiv_source observed=2026-08-16T11:01:39.832116Z digest=sha256:47f9e19577f426348356f125777504f897af6a0de5f6ba5b73fd76081a2df9a7

Observation d3d9a890-367e-4753-b7db-98dd3c0c463c · inbound

The Leaderboard Illusion cites this paper.

The Leaderboard Illusion Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 54

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no resolver link, observed 2026-08-16T05:22:55.548240Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:22:55.548240Z digest=sha256:369de3ef74f90f03277d98455a16afd8030cd766f186f331d7b1444bd00abce0

Observation 505f286c-531a-419f-b90c-58386211ef30 · inbound

Can Global XAI Methods Reveal Injected Behaviours in LLMs? SHAP vs Rule Extraction vs RuleSHAP cites this paper.

Can Global XAI Methods Reveal Injected Behaviours in LLMs? SHAP vs Rule Extraction vs RuleSHAP Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 24

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no resolver link, observed 2026-08-15T21:01:51.836687Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:01:51.836687Z digest=sha256:3ac07518fc23b4bed4a0b9a3738b2cd700a8bf28f49c0b0b7720b7feaebb039f

Observation 2f4d8d5a-931a-4bb6-81bc-60471a111347 · inbound

Beyond the Surface: Measuring Self-Preference in LLM Judgments cites this paper.

Beyond the Surface: Measuring Self-Preference in LLM Judgments Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 22

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no resolver link, observed 2026-08-07T11:26:03.842968Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:26:03.842968Z digest=sha256:97ae2dbbd752e0fd6452011ede4462b135d167eb567bdfdc1ba90b3f2b32be71

Observation 6c134385-792b-4c51-9ea6-155b1800f4e3 · inbound

AbsenceBench: Language Models Can't Tell What's Missing cites this paper.

AbsenceBench: Language Models Can't Tell What's Missing Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 22

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no resolver link, observed 2026-08-07T04:13:17.718512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:13:17.718512Z digest=sha256:ec6b4847bc9a645d063885c61f72395857adfeb0c44695deb725ea5b70c614b2

Observation 4568b5f1-b150-4c37-96a1-ad7f735d3388 · inbound

CRISP: Complex Reasoning with Interpretable Step-based Plans cites this paper.

CRISP: Complex Reasoning with Interpretable Step-based Plans Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 2023

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no resolver link, observed 2026-08-06T19:01:31.053765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:01:31.053765Z digest=sha256:761aac2d6d0b7b0f29d7f0f5a48bd72635743a2e99665f2f1bd2fdb4fc2c7410

Observation 602d4ffe-c342-4bef-9e26-f28960e02120 · inbound

Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming cites this paper.

Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 46

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no resolver link, observed 2026-08-06T11:45:41.064778Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:45:41.064778Z digest=sha256:1f2a1e531be53e7e818028aa396aedd3eb04eb9a2a1e5762b23cc6c69ce37e1e

Observation 44abe90e-85c8-43a4-9e08-15a1b0802d92 · inbound

Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge cites this paper.

Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 12

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no resolver link, observed 2026-08-05T22:40:42.206258Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:40:42.206258Z digest=sha256:f3b07deed57e6cf1f6c0d540e0c7b2133463a523cbca1d8091ebb49a7992a560

Observation a1b445b0-1406-4459-b511-3d2c5ce62956 · inbound

Can You Trick the Grader? Adversarial Persuasion of LLM Judges cites this paper.

Can You Trick the Grader? Adversarial Persuasion of LLM Judges Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 20

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no resolver link, observed 2026-08-05T21:55:58.213182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T21:55:58.213182Z digest=sha256:ed8bc78a5273676abf90ac44c50377fe6401e6c55bb443bc166196aaa35d2ce8

Observation 4e1e2dec-7704-4b8c-935e-200e8f2c817e · inbound

Effectively obtaining acoustic, visual and textual data from videos cites this paper.

Effectively obtaining acoustic, visual and textual data from videos Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 48

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no resolver link, observed 2026-08-05T05:01:36.732735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:01:36.732735Z digest=sha256:230a63c0c124ec2d40e45e811c2f83ef82154db345cd039d1eccfcbba62df874

Observation e4a5ec78-d9dc-4d66-ba76-3f0446d240da · inbound

Testing chatbots on the creation of encoders for audio conditioned image generation cites this paper.

Testing chatbots on the creation of encoders for audio conditioned image generation Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 48

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no resolver link, observed 2026-08-04T21:25:26.892235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:25:26.892235Z digest=sha256:9ed6d6a0f25c032112957827e46deb5b79debaffd13cedae0b19d83534f56d64

Observation 038f4fa5-de01-4194-bad5-b298963f42eb · inbound

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models cites this paper.

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 8

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metadata mismatch
arxiv_id, observed 2026-05-11T00:50:50.481371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T18:18:19.955943Z digest=sha256:aaf3a97f57ed2e7fbd90e1120e85e6a8bd26318c55554c9c112bd8b9f9ccbb6c

Observation b59a23e2-396e-4e0c-a714-32830efcc736 · inbound

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models cites this paper.

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 8

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no resolver link, observed 2026-08-02T16:40:55.426512Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:40:55.426512Z digest=sha256:7c96f322979ebfa443b4c5d1cd81281f9f234ad4b45ddcd746dcbb90ce0c6900

Observation 8ed94691-671b-45a0-9090-854487c94667 · inbound

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models cites this paper.

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 8

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unresolved
no resolver link, observed 2026-08-04T05:36:43.332913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:36:43.332913Z digest=sha256:fd60d6a799242aad3edd2df5dda67c309751c5293012e54fdbbc0c430f895043

Observation 38c552b8-0b23-44f9-86b9-13366418ef4a · inbound

Diagnosing LLM Judge Reliability: Conformal Prediction Sets and Transitivity Violations cites this paper.

Diagnosing LLM Judge Reliability: Conformal Prediction Sets and Transitivity Violations Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 10

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arxiv_id, observed 2026-05-10T10:44:37.607656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-10T10:41:21.406201Z digest=sha256:f08c1b82b6920337a3485cdc2c14af770ade9803c4a4f4a2af7f8a04d9fe2162

Observation 2ffbd726-6c6a-476d-9f0e-873e74becc45 · inbound

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines cites this paper.

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 10

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arxiv_id, observed 2026-05-11T20:41:13.976357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T08:14:18.535385Z digest=sha256:5597675e73abb541b89d3b7a61beaacf8ea8e31823222191c130f02a44782a42

Observation e1a4976e-a1e9-4a7e-94f5-0d076211b651 · inbound

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning cites this paper.

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 55

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arxiv_id, observed 2026-05-09T06:35:39.077576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T18:19:55.849451Z digest=sha256:b2dbbbf91df74f7f11f2506640f7e6f1445db66590a30b160dd5d5647bbf0d7c

Observation 66475279-6144-48ed-9d7e-c63011334597 · inbound

Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps cites this paper.

Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 12

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arxiv_id, observed 2026-05-20T12:33:16.779705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T12:32:22.536994Z digest=sha256:ae75c80322a0df50909e829f109f230471b6c9c3f89bd5303d9cdccd8bbc06ac

Observation 8bbb5c07-bfda-4855-9660-e75ed527d963 · inbound

Does Capability Transfer to Subjective Behavior -- and Would Our Instruments Tell Us? A Self-Evolving, Trust-by-Construction Evaluation Paradigm cites this paper.

Does Capability Transfer to Subjective Behavior -- and Would Our Instruments Tell Us? A Self-Evolving, Trust-by-Construction Evaluation Paradigm Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 63

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arxiv_id, observed 2026-06-29T13:03:26.715349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T12:54:36.818698Z digest=sha256:5520afe838dd9fb98b028b9ad388073f60a644ae0e1968c1ab2eee9d26e710ed

Observation fb9f1fd1-16a0-48c7-81b5-28a198b0db93 · inbound

Show, Don't TELL: Explainable AI-Generated Text Detection cites this paper.

Show, Don't TELL: Explainable AI-Generated Text Detection Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 4

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arxiv_id, observed 2026-06-29T13:03:26.555612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T12:56:04.003337Z digest=sha256:88fa9c9e7a060ba7e273652a141df6bd709a65c1f09687c61b5637045b9cd2ab

Observation 50aad0d0-743e-43ca-9fad-4a0f00ca67f3 · inbound

Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task? cites this paper.

Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task? Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 22

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arxiv_id, observed 2026-06-30T06:04:21.556059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-30T05:59:58.183264Z digest=sha256:f71ee54f9bd533934a79a80722ae2694c9951131b6ab5a33e636c08c235da31c

Observation 1892a6d9-f0ed-461b-86c8-9c57c92a65c1 · inbound

LLM-as-a-Verifier: A General-Purpose Verification Framework cites this paper.

LLM-as-a-Verifier: A General-Purpose Verification Framework Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 65

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local_arxiv, observed 2026-07-07T12:53:50.369284Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-07T12:47:29.552283Z digest=sha256:cd1a2b2e2ba79ade0652a83ebd70a680f678ef42b1e66eb55b2e195067c219d4

Observation c9b73bbf-03de-4ba3-b178-d538abc065d4 · inbound

LLM-as-a-Verifier: A General-Purpose Verification Framework cites this paper.

LLM-as-a-Verifier: A General-Purpose Verification Framework Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 65

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no resolver link, observed 2026-07-11T07:02:51.850836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T07:02:51.850836Z digest=sha256:06b0c810642def3db1132a54ef3757db313da81ab5d5f57f64d4875e9839aa44

Observation cb7ec13a-8c12-44aa-9f13-a015ba53d632 · inbound

AMT-X: Phase-Structured Multi-Turn Red-Teaming with Checklist-Gated Evaluation cites this paper.

AMT-X: Phase-Structured Multi-Turn Red-Teaming with Checklist-Gated Evaluation Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 14

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no resolver link, observed 2026-07-14T06:40:17.865408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:40:17.865408Z digest=sha256:63c2fe45e0bb3c6cf9e9e774896c485bfdd7facf6e38dfb564ccac45796f796a

Observation 2cb7b65c-3a5a-4d79-9294-95f4a01daa4d · inbound

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias cites this paper.

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 21

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no resolver link, observed 2026-07-14T02:33:34.084111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T02:33:34.084111Z digest=sha256:b2e671f306b73a809c5881788d6b2f90b9289b79ab5b1d6c10dbcca7c77a583c

Observation 48c6a736-6094-48ba-be94-2cf8e6e86dbc · inbound

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces cites this paper.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 39

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no resolver link, observed 2026-08-02T16:42:05.597565Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T16:42:05.597565Z digest=sha256:8bdb7455e3ba3379f594352051c22760a4c87ad5939f09198ca27fe6f259f71f